Mount St. Helens (MSH) lies in the forearc of the Cascades where conditions should be too cold for volcanism. To better understand thermal conditions and magma pathways beneath MSH, data from a dense broadband array are used to produce high‐resolution tomographic images of the crust and upper mantle. Rayleigh‐wave phase‐velocity maps and three‐dimensional images of shear velocity (Vs), generated from ambient noise and earthquake surface waves, show that west of MSH the middle‐lower crust is anomalously fast (3.95 ± 0.1 km/s), overlying an anomalously slow uppermost mantle (4.0–4.2 km/s). This combination renders the forearc Moho weak to invisible, with crustal velocity variations being a primary cause; fast crust is necessary to explain the absent Moho. Comparison with predicted rock velocities indicates that the fast crust likely consists of gabbros and basalts of the Siletzia terrane, an accreted oceanic plateau. East of MSH where magmatism is abundant, middle‐lower crust Vs is low (3.45–3.6 km/s), consistent with hot and potentially partly molten crust of more intermediate to felsic composition. This crust overlies mantle with more typical wave speeds, producing a strong Moho. The sharp boundary in crust and mantle Vs within a few kilometers of the MSH edifice correlates with a sharp boundary from low heat flow in the forearc to high arc heat flow and demonstrates that the crustal terrane boundary here couples with thermal structure to focus lateral melt transport from the lower crust westward to arc volcanoes.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2019JB017836","usgsCitation":"Crosbie, K., Abers, G.A., Mann, M.E., Janiszewski, H.A., Creager, K.C., Ulberg, C.W., and Moran, S.C., 2020, Shear velocity structure from ambient noise and teleseismic surface wave tomography in the Cascades around Mount St. Helens: Journal of Geophysical Research, v. 124, no. 8, p. 8358-8375, https://doi.org/10.1029/2019JB017836.","productDescription":"18 p.","startPage":"8358","endPage":"8375","ipdsId":"IP-107648","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":458727,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2019jb017836","text":"Publisher Index Page"},{"id":379510,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Mt. St. Helens","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.3876953125,\n 46.02176059146292\n ],\n [\n -121.95098876953125,\n 46.02176059146292\n ],\n [\n -121.95098876953125,\n 46.326068311712596\n ],\n [\n -122.3876953125,\n 46.326068311712596\n ],\n [\n -122.3876953125,\n 46.02176059146292\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"124","issue":"8","noUsgsAuthors":false,"publicationDate":"2019-08-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Crosbie, Kayla","contributorId":243333,"corporation":false,"usgs":false,"family":"Crosbie","given":"Kayla","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":802074,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Abers, Geoff A. 0000-0003-0704-2097","orcid":"https://orcid.org/0000-0003-0704-2097","contributorId":243334,"corporation":false,"usgs":false,"family":"Abers","given":"Geoff","email":"","middleInitial":"A.","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":802075,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mann, Michael Everett 0000-0001-8418-078X","orcid":"https://orcid.org/0000-0001-8418-078X","contributorId":243335,"corporation":false,"usgs":false,"family":"Mann","given":"Michael","email":"","middleInitial":"Everett","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":802076,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Janiszewski, Helen A. 0000-0003-1425-7969","orcid":"https://orcid.org/0000-0003-1425-7969","contributorId":243336,"corporation":false,"usgs":false,"family":"Janiszewski","given":"Helen","email":"","middleInitial":"A.","affiliations":[{"id":30217,"text":"Carnegie Institution for Science","active":true,"usgs":false}],"preferred":false,"id":802077,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Creager, Kenneth C 0000-0003-4501-7415","orcid":"https://orcid.org/0000-0003-4501-7415","contributorId":221910,"corporation":false,"usgs":false,"family":"Creager","given":"Kenneth","email":"","middleInitial":"C","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":802078,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ulberg, Carl W 0000-0001-6198-809X","orcid":"https://orcid.org/0000-0001-6198-809X","contributorId":221909,"corporation":false,"usgs":false,"family":"Ulberg","given":"Carl","email":"","middleInitial":"W","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":802079,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Moran, Seth C. 0000-0001-7308-9649 smoran@usgs.gov","orcid":"https://orcid.org/0000-0001-7308-9649","contributorId":224629,"corporation":false,"usgs":true,"family":"Moran","given":"Seth","email":"smoran@usgs.gov","middleInitial":"C.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":802080,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70208680,"text":"70208680 - 2020 - In situ benthic nutrient flux and sediment oxygen demand in Barnegat Bay, New Jersey","interactions":[],"lastModifiedDate":"2020-02-24T19:17:26","indexId":"70208680","displayToPublicDate":"2019-07-14T19:13:37","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2220,"text":"Journal of Coastal Research","active":true,"publicationSubtype":{"id":10}},"title":"In situ benthic nutrient flux and sediment oxygen demand in Barnegat Bay, New Jersey","docAbstract":"The U.S. Geological Survey, in cooperation with the New Jersey Department of Environmental Protection, measured sediment oxygen demand (SOD) and benthic nutrient fluxes throughout Barnegat Bay, New Jersey. SOD was determined in situ using chambers equipped with optical dissolved oxygen sensors. The benthic nutrient fluxes of ammonia (NH3), nitrite + nitrate (plus ions; here, referred to as NO32), soluble reactive phosphorous (SRP), and dissolved silica (SiO2) were measured with in situ equilibrium dialysis samplers. Measurements were made at nine stations around the periphery and at three mid-Bay locations from August 2012 to October 2013. The SOD ranged from −1.5 to −8.4 g of oxygen (O2) m−2 d−1. The SOD rates varied as a function of water temperature and followed the van't Hoff rate equation for change in reaction rate with temperature, with a temperature coefficient (Θ) that varied among sites and averaged 1.083. The highest SOD rates in the bay were measured near the mouth of the Toms River embayment. Concentrations in the upper 1 m of sediment pore water were found up to 23 mg N L−1 for NH4+ and 6.7 mg P L−1 for SRP. Maximum measured fluxes into the overlying water were 3.0 × 10−2 g NH3–N m−2 d−1, 7.0 × 10−4 g NO32–N m−2 d−1, 1.9 × 10−3 g P m−2 d−1, and 3.6 × 10−3g SiO2 m−2 d−1. Using the measured benthic N and P fluxes, daily nutrient inputs derived from sediment recycling are shown to be comparable in scale to freshwater tributary inputs to the bay.","language":"English","publisher":"Coastal Education and Research Foundation, Inc","doi":"10.2112/SI78-005.1","usgsCitation":"Wilson, T., and DePaul, V.T., 2020, In situ benthic nutrient flux and sediment oxygen demand in Barnegat Bay, New Jersey: Journal of Coastal Research, v. 78, p. 46-59, https://doi.org/10.2112/SI78-005.1.","productDescription":"14 p.","startPage":"46","endPage":"59","ipdsId":"IP-069751","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":437221,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7KD1WC3","text":"USGS data release","linkHelpText":"Benthic pore water and sediment data Barnegat Bay, New Jersey, 2012-2013"},{"id":372593,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Jersey","otherGeospatial":"Barnegat Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.22019958496094,\n 39.665970875883175\n ],\n [\n -74.1796875,\n 39.6458824809188\n ],\n [\n -74.09660339355469,\n 39.768436410838426\n ],\n [\n -74.08561706542969,\n 39.92132255884663\n ],\n [\n -74.10621643066406,\n 39.95185892663005\n ],\n [\n -74.12200927734375,\n 39.93817189499188\n ],\n [\n -74.13848876953125,\n 39.8992015115692\n ],\n [\n -74.13986206054688,\n 39.86969567045658\n ],\n [\n -74.14398193359375,\n 39.85072092501597\n ],\n [\n -74.17076110839844,\n 39.82224896999684\n ],\n [\n -74.18792724609375,\n 39.79482037706643\n ],\n [\n -74.1961669921875,\n 39.7631584037253\n ],\n [\n -74.19548034667969,\n 39.74837783143156\n ],\n [\n -74.1796875,\n 39.73676229957947\n ],\n [\n -74.17625427246094,\n 39.72461669561139\n ],\n [\n -74.17556762695312,\n 39.71035608240133\n ],\n [\n -74.19479370117188,\n 39.69345079688953\n ],\n [\n -74.21401977539062,\n 39.67706985250899\n ],\n [\n -74.22225952148438,\n 39.67072779849953\n ],\n [\n -74.22019958496094,\n 39.665970875883175\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"78","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Wilson, Timothy P. 0000-0003-1914-6344","orcid":"https://orcid.org/0000-0003-1914-6344","contributorId":219174,"corporation":false,"usgs":true,"family":"Wilson","given":"Timothy P.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":782978,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"DePaul, Vincent T. 0000-0002-7977-5217 vdepaul@usgs.gov","orcid":"https://orcid.org/0000-0002-7977-5217","contributorId":2778,"corporation":false,"usgs":true,"family":"DePaul","given":"Vincent","email":"vdepaul@usgs.gov","middleInitial":"T.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":782979,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70210198,"text":"70210198 - 2020 - Estimating visitor use and economic contributions of National Park visitor spending","interactions":[],"lastModifiedDate":"2020-06-03T16:02:49.893141","indexId":"70210198","displayToPublicDate":"2019-07-12T11:01:28","publicationYear":"2020","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Estimating visitor use and economic contributions of National Park visitor spending","docAbstract":"This chapter provides an overview of the National Park Service (NPS) methods for estimating visitor spending and calculating economic contributions of visitor spending in terms of jobs supported, wage and labor income, and total economic activity. The Visitor Spending Effects model combines visitor spending patterns and trip characteristic data with visitor use data to estimate total visitor spending. Economic contributions measure the total economic activity within a regional economy stemming from visitor spending, and include the effects of spending by both local visitors who live within gateway regions and non-local visitors who travel to NPS sites from outside of gateway regions. The Social Science Program collaborates with individual parks to develop visitor counting instructions that contain the procedures for measuring, compiling, and recording required visitor use data. Visitor surveys are used to collect the essential visitor spending and trip characteristic data necessary for developing spending profiles to represent distinct visitor spending patterns for each park.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Valuing U.S. National Parks and Programs","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Routledge","doi":"10.4324/9781351055789","collaboration":"National Park Service","usgsCitation":"Koontz, L., and Cullinane Thomas, C., 2020, Estimating visitor use and economic contributions of National Park visitor spending, chap. of Valuing U.S. National Parks and Programs, 13 p., https://doi.org/10.4324/9781351055789.","productDescription":"13 p.","ipdsId":"IP-099361","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":375349,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2019-07-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Koontz, Lynne koontzl@usgs.gov","contributorId":2174,"corporation":false,"usgs":false,"family":"Koontz","given":"Lynne","email":"koontzl@usgs.gov","affiliations":[{"id":7016,"text":"Environmental Quality Division, National Park Service, Fort Collins, Colorado","active":true,"usgs":false}],"preferred":false,"id":789508,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cullinane Thomas, Catherine 0000-0001-8168-1271 ccullinanethomas@usgs.gov","orcid":"https://orcid.org/0000-0001-8168-1271","contributorId":141097,"corporation":false,"usgs":true,"family":"Cullinane Thomas","given":"Catherine","email":"ccullinanethomas@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":789509,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70204205,"text":"70204205 - 2020 - A comprehensive approach uncovers hidden diversity in freshwater mussels (Bivalvia: Unionidae) with the description of a novel species","interactions":[],"lastModifiedDate":"2020-01-20T12:33:07","indexId":"70204205","displayToPublicDate":"2019-07-02T15:11:04","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1242,"text":"Cladistics","active":true,"publicationSubtype":{"id":10}},"title":"A comprehensive approach uncovers hidden diversity in freshwater mussels (Bivalvia: Unionidae) with the description of a novel species","docAbstract":"Major geological processes have shaped biogeographical patterns of riverine biota. The Edwards Plateau of central Texas, USA, exhibits unique aquatic communities and endemism, including several species of freshwater mussels. Lampsilis bracteata (Gould, 1855) is endemic to the Edwards Plateau region; however, its phylogenetic relationship with other species in the Gulf coastal rivers and Mississippi River basin is unknown. We evaluated phylogenetic relationships, shell morphologies and soft anatomy characters of L. bracteata and a closely related congener, Lampsilis hydiana (Lea, 1838) throughout their ranges. Our results showed the presence of an undescribed species: Lampsilis bergmanni sp.n. Lampsilis bracteata and L. bergmanni sp.n. share similar shell morphologies and soft anatomy characters; however, they are genetically distinct. Geological processes, such as faulting and sea‐level changes during the Miocene to Pliocene, are likely to have facilitated diversification of Lampsilis species, resulting in isolation of L. bracteata on the Edwards Plateau and diversification between L. bergmanni sp.n. and L. hydiana. We conclude that L. bracteata range is restricted to the Colorado River basin, whereas L. bergmanni sp.n. occurs only in upstream reaches of the Guadalupe River basin. Conservation actions are warranted for both species due to their restricted distributions and potential anthropogenic threats.
","language":"English","publisher":"Wiley","doi":"10.1111/cla.12386","usgsCitation":"Inoue, K., Harris, J.L., Robertson, C., Johnson, N., and Randklev, C.R., 2020, A comprehensive approach uncovers hidden diversity in freshwater mussels (Bivalvia: Unionidae) with the description of a novel species: Cladistics, v. 36, no. 1, p. 88-113, https://doi.org/10.1111/cla.12386.","productDescription":"26 p.","startPage":"88","endPage":"113","ipdsId":"IP-103503","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":458729,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/cla.12386","text":"Publisher Index Page"},{"id":365488,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Texas","otherGeospatial":"Edwards Plateau","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -100.5029296875,\n 29.11377539511439\n ],\n [\n -96.2841796875,\n 29.11377539511439\n ],\n [\n -96.2841796875,\n 32.76880048488168\n ],\n [\n -100.5029296875,\n 32.76880048488168\n ],\n [\n -100.5029296875,\n 29.11377539511439\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"36","issue":"1","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2019-07-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Inoue, Kentaro","contributorId":202526,"corporation":false,"usgs":false,"family":"Inoue","given":"Kentaro","email":"","affiliations":[{"id":6747,"text":"Texas A&M University","active":true,"usgs":false}],"preferred":false,"id":765981,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Harris, John L.","contributorId":201225,"corporation":false,"usgs":false,"family":"Harris","given":"John","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":765980,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Robertson, Clint","contributorId":206217,"corporation":false,"usgs":false,"family":"Robertson","given":"Clint","affiliations":[{"id":37288,"text":"Texas Parks and Wildife","active":true,"usgs":false}],"preferred":false,"id":765982,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Johnson, Nathan 0000-0001-5167-1988","orcid":"https://orcid.org/0000-0001-5167-1988","contributorId":216879,"corporation":false,"usgs":true,"family":"Johnson","given":"Nathan","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":765979,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Randklev, Charles R.","contributorId":202530,"corporation":false,"usgs":false,"family":"Randklev","given":"Charles","email":"","middleInitial":"R.","affiliations":[{"id":36313,"text":"Texas A&M","active":true,"usgs":false}],"preferred":false,"id":765983,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70208113,"text":"70208113 - 2020 - Infection at an ecotone: Cross‐system foraging increases satellite parasites but decreases core parasites in raccoons","interactions":[],"lastModifiedDate":"2020-01-27T19:18:17","indexId":"70208113","displayToPublicDate":"2019-07-01T19:16:51","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1465,"text":"Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Infection at an ecotone: Cross‐system foraging increases satellite parasites but decreases core parasites in raccoons","docAbstract":"Ecotones can increase free-living species richness, but little is known about how parasites respond to ecotones. Here we use parasite communities in raccoons (Procyon lotor) to test the hypothesis that parasite communities can be divided into core and satellite species, each with fundamentally different responses to ecotones. We used published parasite surveys to classify parasites as common core or rare satellite species and then surveyed raccoons in coastal California to examine how proximity to two aquatic ecotones altered parasite communities. Raccoons near ecotones had more satellite and fewer core parasite species. Specifically, the marine ecotone increased parasite diversity by adding satellite species to a persistent core community, whereas the freshwater ecotone shifted the community from core to satellite species without a net change in parasite richness. We hypothesize that increased parasite richness at the marine ecotone resulted from increased diet diversity, but that raccoons were sinks for some parasites. Increased exposure to rare parasites at ecotones has implications for wildlife health and provides insight into observed associations between ecotones and emerging disease.","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecy.2808","usgsCitation":"Weinstein, S.B., Van Wert, J.C., Kinsella, M., Tkach, V.V., and Lafferty, K.D., 2020, Infection at an ecotone: Cross‐system foraging increases satellite parasites but decreases core parasites in raccoons: Ecology, no. 100, e02808, https://doi.org/10.1002/ecy.2808.","productDescription":"e02808","ipdsId":"IP-106751","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":458731,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecy.2808","text":"Publisher Index Page"},{"id":371614,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -125.0244140625,\n 42.114523952464246\n ],\n [\n -125.1123046875,\n 40.66397287638688\n ],\n [\n -124.60693359374999,\n 39.30029918615029\n ],\n [\n -123.26660156249999,\n 37.17782559332976\n ],\n [\n -121.46484375,\n 34.57895241036948\n ],\n [\n -119.53125,\n 32.82421110161336\n ],\n [\n -117.42187500000001,\n 32.54681317351514\n ],\n [\n -116.45507812500001,\n 32.89803818160521\n ],\n [\n -118.5205078125,\n 34.08906131584994\n ],\n [\n -120.43212890625,\n 35.65729624809628\n ],\n [\n -121.86035156249999,\n 38.37611542403604\n ],\n [\n -123.4423828125,\n 40.48038142908172\n ],\n [\n -123.26660156249999,\n 42.01665183556825\n ],\n [\n -125.0244140625,\n 42.114523952464246\n ]\n ]\n ]\n }\n }\n ]\n}","issue":"100","edition":"9","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2019-07-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Weinstein, Sara B.","contributorId":141028,"corporation":false,"usgs":false,"family":"Weinstein","given":"Sara","email":"","middleInitial":"B.","affiliations":[{"id":7168,"text":"UCSB","active":true,"usgs":false}],"preferred":false,"id":780526,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Van Wert, Jacey C.","contributorId":221858,"corporation":false,"usgs":false,"family":"Van Wert","given":"Jacey","email":"","middleInitial":"C.","affiliations":[{"id":37180,"text":"UC Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":780527,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kinsella, Mike","contributorId":221859,"corporation":false,"usgs":false,"family":"Kinsella","given":"Mike","email":"","affiliations":[{"id":40444,"text":"Helm West Laboratory, Missoula, MT","active":true,"usgs":false}],"preferred":false,"id":780528,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Tkach, Vasyl V.","contributorId":190351,"corporation":false,"usgs":false,"family":"Tkach","given":"Vasyl","email":"","middleInitial":"V.","affiliations":[{"id":52695,"text":"Department of Biology, University of North Dakota, Grand Forks, ND 58201, USA","active":true,"usgs":false}],"preferred":false,"id":780529,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lafferty, Kevin D. 0000-0001-7583-4593 klafferty@usgs.gov","orcid":"https://orcid.org/0000-0001-7583-4593","contributorId":1415,"corporation":false,"usgs":true,"family":"Lafferty","given":"Kevin","email":"klafferty@usgs.gov","middleInitial":"D.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":780525,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70208877,"text":"70208877 - 2020 - Investigating bedload transport under asymmetrical waves using a coupled ocean-wave model","interactions":[],"lastModifiedDate":"2020-03-04T16:45:11","indexId":"70208877","displayToPublicDate":"2019-06-30T16:39:32","publicationYear":"2020","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Investigating bedload transport under asymmetrical waves using a coupled ocean-wave model","docAbstract":"Transport by asymmetrical wave motions plays a key role in cross-shore movement of sand, which is important for bar migration, exchange through tidal inlets, and beach recovery after storms. We have implemented a modified version of the SANTOSS formulation in the three-dimensional open-source Coupled-Ocean-Atmosphere-Wave-Sediment Transport (COAWST) modeling framework. The calculation of bedload transport requires inputs that include: water depth, bulk wave statistics (significant wave height, wave period, wave orbital velocity), current velocity at the edge of the wave boundary layer, and sediment density and grain size. While the coupled ocean-wave model computes water density, depth, and bulk wave statistics, we implement a method to calculate current velocity assuming a log profile and using the Madsen formulations for wave-current bottom boundary layer flows. We investigate the sensitivity of the calculation of near-bottom current velocity to model choices and its influence on cross-shore bedload transport. 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In this paper, the skill of the XBeach model to predict hurricane-induced barrier island overwash, dune erosion, and breaching is demonstrated. The location of the breach is predicted correctly if bottom roughness based on land cover is used to calculate bed shear stresses. While the dunes are initially lowered by wave attack and surge from the ocean side, the main driver for breach formation is the water level difference between the back-barrier and nearshore, causing an ocean-directed outflow of water after the peak of the storm.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Coastal sediments 2019: Proceedings of the 9th international conference","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"International Conference on Coastal Sediments 2019","conferenceDate":"May 27-31, 2019","conferenceLocation":"Tampa/St. Petersburg, FL","language":"English","publisher":"World Scientific","doi":"10.1142/9789811204487_0012","usgsCitation":"Quataert, E., van der Lugt, M., Sherwood, C.R., van Oormondt, M., and van Dongeran, A., 2020, Modeling the morphological response of a barrier island to Hurricane Matthew, in Coastal sediments 2019: Proceedings of the 9th international conference, Tampa/St. Petersburg, FL, May 27-31, 2019, p. 128-138, https://doi.org/10.1142/9789811204487_0012.","productDescription":"11 p.","startPage":"128","endPage":"138","ipdsId":"IP-105247","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":372928,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Matanzas Inlet","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.19171142578125,\n 29.621818021144485\n ],\n [\n -81.24629974365234,\n 29.767059606099\n ],\n [\n -81.26106262207031,\n 29.806688644587382\n ],\n [\n -81.28921508789062,\n 29.80609283540296\n ],\n [\n -81.25179290771484,\n 29.719364794202505\n ],\n [\n -81.23085021972656,\n 29.65434412369176\n ],\n [\n -81.21437072753906,\n 29.608088257406806\n ],\n [\n -81.19171142578125,\n 29.621818021144485\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationDate":"2019-05-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Quataert, Ellen","contributorId":149000,"corporation":false,"usgs":false,"family":"Quataert","given":"Ellen","affiliations":[{"id":17614,"text":"Delft University of Technology","active":true,"usgs":false}],"preferred":false,"id":783921,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"van der Lugt, Marlies","contributorId":221148,"corporation":false,"usgs":false,"family":"van der Lugt","given":"Marlies","email":"","affiliations":[{"id":40335,"text":"Detlares","active":true,"usgs":false}],"preferred":false,"id":783922,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sherwood, Christopher R. 0000-0001-6135-3553 csherwood@usgs.gov","orcid":"https://orcid.org/0000-0001-6135-3553","contributorId":2866,"corporation":false,"usgs":true,"family":"Sherwood","given":"Christopher","email":"csherwood@usgs.gov","middleInitial":"R.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":783923,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"van Oormondt, Maarten","contributorId":223048,"corporation":false,"usgs":false,"family":"van Oormondt","given":"Maarten","email":"","affiliations":[],"preferred":false,"id":783924,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"van Dongeran, Ap","contributorId":176244,"corporation":false,"usgs":false,"family":"van Dongeran","given":"Ap","email":"","affiliations":[],"preferred":false,"id":783925,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70208808,"text":"70208808 - 2020 - Assessing the chemistry and bioavailability of dissolved organic matter from glaciers and rock glaciers","interactions":[],"lastModifiedDate":"2020-03-02T12:50:47","indexId":"70208808","displayToPublicDate":"2019-06-26T12:45:46","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2320,"text":"Journal of Geophysical Research: Biogeosciences","active":true,"publicationSubtype":{"id":10}},"title":"Assessing the chemistry and bioavailability of dissolved organic matter from glaciers and rock glaciers","docAbstract":"As glaciers thaw in response to warming, they release dissolved organic matter (DOM) to alpine lakes and streams. The United States contains an abundance of both alpine glaciers and rock glaciers. Differences in DOM composition and bioavailability between glacier types, like rock and ice glaciers, remain undefined. To assess differences in glacier and rock glacier DOM we evaluated bioavailability and molecular composition of DOM from four alpine catchments each with a glacier and a rock glacier at their headwaters. We assessed bioavailability of DOM by incubating each DOM source with a common microbial community and evaluated chemical characteristics of DOM before and after incubation using untargeted gas chromatography–mass spectrometry‐based metabolomics. Prior to incubations, ice glacier and rock glacier DOM had similar C:N ratios and chemical diversity, but differences in DOM composition. Incubations with a common microbial community showed that DOM from ice glacier meltwaters contained a higher proportion of bioavailable DOM and resulted in greater bacterial growth efficiency. After incubation, DOM composition from each source was statistically indistinguishable. This study provides an example of how MS‐based metabolomics can be used to assess effects of DOM composition on differences in bioavailability of DOM. Furthermore, it illustrates the importance of microbial metabolism in structuring composition of DOM. Even though rock glaciers had significantly less bioavailable DOM than ice glaciers, both glacial types still have potential to be important sources of bioavailable DOM to alpine headwaters over the coming decades.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2018JG004874","usgsCitation":"Fegel, T.S., Boot, C.M., Broeckling, C.D., Baron, J., and Hall, E., 2020, Assessing the chemistry and bioavailability of dissolved organic matter from glaciers and rock glaciers: Journal of Geophysical Research: Biogeosciences, v. 124, no. 7, p. 1988-2004, https://doi.org/10.1029/2018JG004874.","productDescription":"17 p.","startPage":"1988","endPage":"2004","ipdsId":"IP-092157","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":458738,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2018jg004874","text":"Publisher Index Page"},{"id":437223,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9CW05WB","text":"USGS data release","linkHelpText":"Water chemistry and land cover attributes for The Loch and Sky Pond, Rocky Mountain National Park"},{"id":437222,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9A0JNP9","text":"USGS data release","linkHelpText":"Laboratory Incubation results from 2015 for bacterial cell counts, carbon use efficiency, growth efficiency, and dissolved organic matter chemistry from four glacier outflows and four rock glacier outflows in Colorado"},{"id":372779,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Arapaho Glacier, Arapaho Rock Glacier","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -105.84915161132812,\n 40.04969396696316\n ],\n [\n -105.43716430664062,\n 40.04969396696316\n ],\n [\n -105.43716430664062,\n 40.445379415215285\n ],\n [\n -105.84915161132812,\n 40.445379415215285\n ],\n [\n -105.84915161132812,\n 40.04969396696316\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"124","issue":"7","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2019-07-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Fegel, Timothy S.","contributorId":167462,"corporation":false,"usgs":false,"family":"Fegel","given":"Timothy","email":"","middleInitial":"S.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":783471,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Boot, Claudia M.","contributorId":213577,"corporation":false,"usgs":false,"family":"Boot","given":"Claudia","email":"","middleInitial":"M.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":783472,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Broeckling, Corey D.","contributorId":222912,"corporation":false,"usgs":false,"family":"Broeckling","given":"Corey","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":783490,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Baron, Jill 0000-0002-5902-6251 jill_baron@usgs.gov","orcid":"https://orcid.org/0000-0002-5902-6251","contributorId":194124,"corporation":false,"usgs":true,"family":"Baron","given":"Jill","email":"jill_baron@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":783470,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hall, Edward K","contributorId":216901,"corporation":false,"usgs":false,"family":"Hall","given":"Edward K","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":783473,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70204052,"text":"70204052 - 2020 - Establishing genome sizes of focal fishery and aquaculture species along Baja California, Mexico","interactions":[],"lastModifiedDate":"2020-06-04T16:32:07.115911","indexId":"70204052","displayToPublicDate":"2019-06-25T09:50:04","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1325,"text":"Conservation Genetics Resources","active":true,"publicationSubtype":{"id":10}},"title":"Establishing genome sizes of focal fishery and aquaculture species along Baja California, Mexico","docAbstract":"Genome size—the total haploid content of nuclear DNA— is constant in all cells in individuals within a species, but differs among species. Consequently, the genome size is a quantifiable genetic signature that not only characterizes a species, but it can reflect chromatin modifications, which play fundamental roles in most biological processes that are involved in the manipulation and expression of DNA. This characteristic makes the genome size a crucial parameter for genetic research on endemic aquatic species and for genetic manipulations in aquaculture species. Technologies for genetic assessments and improvements applied to fishery and aquaculture species use genome size values as a means by which hybrids, polyploids, and sex can be identified, when sex chromosomes exist. The objectives of this study were to determine genome sizes of aquatic species with economic and biological importance along the Pacific coast of Mexico, as well as to identify the appropriate reference standards for use in this study. Blood, hemolymph or milt were collected from 10 species occurring along the coast of Baja California: Sablefish Anoplopoma fimbria, Black Snapper Lutjanus novemfasciatus, California Halibut Paralichthys californicus, Pacific Sardine Sardinops sagax, Flag Rockfish Sebastes rubrivinctus, Starry Rockfish Sebastes constellatus, Totoaba Totoaba macdonaldi, Whiteleg Shrimp Litopenaeus vannamei and two Yellowtail Seriola lalandi and S. dorsalis. Nuclear DNA was stained with propidium iodide solution and the genome size was determined by flow cytometry, with results ranging from 0.61 pg (1.22 pg/diploid cell) to 2.59 pg (5.18 pg/diploid cell), with the smallest value in Sablefish and the largest in the Whiteleg Shrimp. No significant differences were detected (P ≤ 0.05) among individuals of the same species; the likely reason behind any dissimilar DNA content values with those from the literature were differences in methodologies or variations in genetics. Red-ear Slider Turtle Trachemys scripta elegans 2.65 pg (5.30 pg/diploid cell) and Red Junglefowl Gallus gallus 1.27 pg (2.54 pg/diploid cell) were chosen as the standards for reference values. These results establish the basis for the Mexican National Aquatic Genetic Resources project supporting genetic improvements for aquaculture and conservation status parameters for fisheries species.
","language":"English","publisher":"Springer Nature","doi":"10.1007/s12686-019-01105-y","usgsCitation":"del Mar Ochoa-Saloma, C., Jenkins, J.A., Segovia, M.A., Del Rio-Portilla, M.A., and Paniagua-Chavez, C.G., 2020, Establishing genome sizes of focal fishery and aquaculture species along Baja California, Mexico: Conservation Genetics Resources, v. 12, p. 301-309, https://doi.org/10.1007/s12686-019-01105-y.","productDescription":"9 p.","startPage":"301","endPage":"309","ipdsId":"IP-089376","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":365244,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Mexico","otherGeospatial":"Baja California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.158203125,\n 32.58384932565662\n ],\n [\n -117.50976562499999,\n 31.914867503276223\n ],\n [\n -116.8505859375,\n 30.90222470517144\n ],\n [\n -115.13671875,\n 28.57487404744697\n ],\n [\n -115.72998046875,\n 28.420391085674304\n ],\n [\n -114.67529296874999,\n 26.62781822639305\n ],\n [\n -112.8515625,\n 25.740529092773226\n ],\n [\n -112.4560546875,\n 24.56710835257599\n ],\n [\n -111.55517578125,\n 23.765236889758672\n ],\n [\n -109.75341796875,\n 22.329752304376473\n ],\n [\n -108.8525390625,\n 23.221154981846556\n ],\n [\n -109.2919921875,\n 24.627044746156027\n ],\n [\n -111.97265625,\n 27.877928333679495\n ],\n [\n -114.43359375,\n 31.297327991404266\n ],\n [\n -114.60937499999999,\n 31.466153715024294\n ],\n [\n -117.158203125,\n 32.58384932565662\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"12","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2019-06-25","publicationStatus":"PW","contributors":{"authors":[{"text":"del Mar Ochoa-Saloma, Constanza","contributorId":216673,"corporation":false,"usgs":false,"family":"del Mar Ochoa-Saloma","given":"Constanza","email":"","affiliations":[{"id":39498,"text":"Departmento de Acuicultura, Centro de Investigacion Cientifica y de Educacion Superior de Ensenada, Baja California (CICESE)","active":true,"usgs":false}],"preferred":false,"id":765289,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jenkins, Jill A. 0000-0002-5087-0894 jenkinsj@usgs.gov","orcid":"https://orcid.org/0000-0002-5087-0894","contributorId":2710,"corporation":false,"usgs":true,"family":"Jenkins","given":"Jill","email":"jenkinsj@usgs.gov","middleInitial":"A.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":765288,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Segovia, Manuel A.","contributorId":216674,"corporation":false,"usgs":false,"family":"Segovia","given":"Manuel","email":"","middleInitial":"A.","affiliations":[{"id":39498,"text":"Departmento de Acuicultura, Centro de Investigacion Cientifica y de Educacion Superior de Ensenada, Baja California (CICESE)","active":true,"usgs":false}],"preferred":false,"id":765290,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Del Rio-Portilla, Miguel A.","contributorId":216675,"corporation":false,"usgs":false,"family":"Del Rio-Portilla","given":"Miguel","email":"","middleInitial":"A.","affiliations":[{"id":39498,"text":"Departmento de Acuicultura, Centro de Investigacion Cientifica y de Educacion Superior de Ensenada, Baja California (CICESE)","active":true,"usgs":false}],"preferred":false,"id":765291,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Paniagua-Chavez, Carmen G.","contributorId":216676,"corporation":false,"usgs":false,"family":"Paniagua-Chavez","given":"Carmen","email":"","middleInitial":"G.","affiliations":[{"id":39498,"text":"Departmento de Acuicultura, Centro de Investigacion Cientifica y de Educacion Superior de Ensenada, Baja California (CICESE)","active":true,"usgs":false}],"preferred":false,"id":765292,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70204110,"text":"70204110 - 2020 - Hydroseeding tackifiers and dryland moss restoration potential","interactions":[],"lastModifiedDate":"2024-07-17T21:41:12.423442","indexId":"70204110","displayToPublicDate":"2019-06-17T16:45:31","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3271,"text":"Restoration Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Hydroseeding tackifiers and dryland moss restoration potential","docAbstract":"Tackifiers are long‐chain carbon compounds used for soil stabilization and hydroseeding and could provide a vehicle for biological soil crust restoration. We examined the sensitivity of two dryland mosses, Bryum argenteum and Syntrichia ruralis, to three common tackifiers ‐ guar, psyllium, and polyacrylamide (PAM) ‐ at 0.5x, 1.0x, and 2.0x of recommended (x) concentrations for erosion control and revegetation. We measured moss shoot, gemma, and protonema production as well as moss organic matter and bound sand masses as indicators of growth and soil holding ability. We tested sand and tackifier chemistry to investigate potential nutrient and toxicant potential on moss growth. Groups of ten fragments from field‐collected mosses were grown on sand in open petri dishes arranged in a growth chamber in replicated blocks containing each tackifier and concentration combination plus a distilled water control. Bryum (n=10) and Syntrichia (n=9) growth were measured at the end of six and five weeks, respectively. Overall model tests yielded statistically significant results (p<0.001) for every variable in each species. When compared to water, guar tended to decrease growth, psyllium tended to increase growth, and PAM's effects were generally neutral to positive. Within tackifier types, increasing concentrations of guar tended to decrease growth, while increasing concentrations of psyllium tended to increase growth. Changes in PAM concentrations had little effect on growth. Increases in guar and psyllium lowered pH and increased P and K. Psyllium and PAM yielded promising results as potential agents of dispersal and adherence of dryland mosses in field restoration.
","language":"English","publisher":"Wiley","doi":"10.1111/rec.12997","usgsCitation":"Blankenship, W.D., Condon, L.A., and Pyke, D.A., 2020, Hydroseeding tackifiers and dryland moss restoration potential: Restoration Ecology, v. 28, no. S2, p. S127-S138, https://doi.org/10.1111/rec.12997.","productDescription":"12 p.","startPage":"S127","endPage":"S138","ipdsId":"IP-106770","costCenters":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"links":[{"id":458742,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/rec.12997","text":"Publisher Index Page"},{"id":365318,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"28","issue":"S2","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2019-07-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Blankenship, W. Dillon","contributorId":216798,"corporation":false,"usgs":false,"family":"Blankenship","given":"W.","email":"","middleInitial":"Dillon","affiliations":[{"id":39520,"text":"Oregon State University, Department of Botany and Plant Pathology","active":true,"usgs":false}],"preferred":false,"id":765561,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Condon, Lea A. 0000-0002-9357-3881","orcid":"https://orcid.org/0000-0002-9357-3881","contributorId":202908,"corporation":false,"usgs":true,"family":"Condon","given":"Lea","email":"","middleInitial":"A.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":765560,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pyke, David A. 0000-0002-4578-8335 david_a_pyke@usgs.gov","orcid":"https://orcid.org/0000-0002-4578-8335","contributorId":3118,"corporation":false,"usgs":true,"family":"Pyke","given":"David","email":"david_a_pyke@usgs.gov","middleInitial":"A.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":765559,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70221421,"text":"70221421 - 2020 - Upwelling buffers climate change impacts on coral reefs of the eastern tropical Pacific","interactions":[],"lastModifiedDate":"2021-06-15T11:43:50.746984","indexId":"70221421","displayToPublicDate":"2019-06-15T06:40:00","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1465,"text":"Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Upwelling buffers climate change impacts on coral reefs of the eastern tropical Pacific","docAbstract":"Corals of the eastern tropical Pacific live in a marginal and oceanographically dynamic environment. Along the Pacific coast of Panamá, stronger seasonal upwelling in the Gulf of Panamá in the east transitions to weaker upwelling in the Gulf of Chiriquí in the west, resulting in complex regional oceanographic conditions that drive differential coral-reef growth. Over millennial timescales, reefs in the Gulf of Chiriquí recovered more quickly from climatic disturbances compared with reefs in the Gulf of Panamá. In recent decades, corals in the Gulf of Chiriquí have also had higher growth rates than in the Gulf of Panamá. As the ocean continues to warm, however, conditions could shift to favor the growth of corals in the Gulf of Panamá, where upwelling may confer protection from high-temperature anomalies. Here we describe the recent spatial and temporal variability in surface oceanography of nearshore environments in Pacific Panamá and compare those conditions with the dynamics of contemporary coral-reef communities during and after the 2016 coral-bleaching event. Although both gulfs have warmed significantly over the last 150 yr, the annual thermal maximum in the Gulf of Chiriquí is increasing faster, and ocean temperatures there are becoming more variable than in the recent past. In contrast to historical trends, we found that coral cover, coral survival, and coral growth rates were all significantly higher in the Gulf of Panamá. Corals bleached extensively in the Gulf of Chiriquí following the 2015–2016 El Niño event, whereas upwelling in the Gulf of Panamá moderated the high temperatures caused by El Niño, allowing the corals largely to escape thermal stress. As the climate continues to warm, upwelling zones may offer a temporary and localized refuge from the thermal impacts of climate change, while reef growth in the rest of the eastern tropical Pacific continues to decline.
The El Niño–Southern Oscillation (ENSO) represents the largest source of year-to-year global climate variability. While Earth system models suggest a range of possible shifts in ENSO properties under continued greenhouse gas forcing, many centuries of preindustrial climate data are required to detect a potential shift in the properties of recent ENSO extremes. Here we reconstruct the strength of ENSO variations over the last 7,000 years with a new ensemble of fossil coral oxygen isotope records from the Line Islands, located in the central equatorial Pacific. The corals document a significant decrease in ENSO variance of ~20% from 3,000 to 5,000 years ago, coinciding with changes in spring/fall precessional insolation. We find that ENSO variability over the last five decades is ~25% stronger than during the preindustrial. Our results provide empirical support for recent climate model projections showing an intensification of ENSO extremes under greenhouse forcing.
We present the first demonstration of hydraulic tomography (HT) to estimate the three-dimensional (3D) hydraulic conductivity (K) distribution of a fractured aquifer at high-resolution field scale (HRFS), including the fracture network and connectivity through it. We invert drawdown data collected from packer-isolated borehole intervals during 42 pumping tests in a wellfield at the former Naval Air Warfare Center, West Trenton, New Jersey, in the Newark Basin. Five additional tests were reserved for a quality check of HT results. We used an equivalent porous medium forward model and geostatistical inversion to estimate 3D K at high resolution (K blocks <1 m3), using no strict assumptions about K variability or fracture statistics. The resulting 3D K estimate ranges from approximately 0.1 (highest-K fractures) to approximately 10−13 m/s (unfractured mudstone). Important estimated features include: (1) a highly fractured zone (HFZ) consisting of a sequence of high-K bedding-plane fractures; (2) a low-K zone that disrupts the HFZ; (3) several secondary fractures of limited extent; and (4) regions of very low-K rock matrix. The 3D K estimate explains complex drawdown behavior observed in the field. Drawdown tracing and particle tracking simulations reveal a 3D fracture network within the estimated K distribution, and connectivity routes through the network. Model fit is best in the shallower part of the wellfield, with high density of observations and tests. The capabilities of HT demonstrated for 3D fractured aquifer characterization at HRFS may support improved in situ remediation for contaminant source zones, and applications in mining, repository assessment, or geotechnical engineering.
Anadromous Pacific salmon are semelparous, and resource subsidies from spawning adults (marine-derived nutrients, or MDN) benefit juvenile salmonids rearing in freshwater. However, it remains unclear how MDN assimilation relates to spawner abundance within a watershed. To address this, we examined seasonal, watershed-scale patterns of MDN assimilation in rearing coho (Oncorhynchus kisutch) and Chinook (O. tshawytscha) salmon and compared it with spawner biomass and landscape features in a western Alaska watershed with contrasting structural complexity in two sub-drainages. Adult salmon biomass density was estimated from escapement and spawner distribution data, and MDN assimilation in juvenile salmon was estimated via stable isotopes. In the North River, MDN assimilation was lowest in early summer, prior to annual spawning migrations, increased after spawning, and peaked in late winter. In the more complex mainstem Unalakleet River, MDN assimilation was higher but varied minimally from summer through fall before increasing in late fall and winter. Summer MDN assimilation, prior to salmon spawning, was primarily a function of habitat complexity, where MDN was highest in sloughs and the more complex mainstem river. After salmon spawned, fall MDN assimilation was a function of adult pink and Chinook salmon biomass as well as MDN assimilation that occurred prior to spawning (that is, summer MDN), but unrelated to total summer biomass (all salmon species biomass combined). Thus, MDN assimilation by juvenile salmon in the fall was a function of species-specific adult spawner abundance but seasonal patterns of MDN assimilation were masked in complex habitat where summer MDN assimilation remained high.
Accurate age estimates are critical for understanding life histories of fishes and developing management strategies for fish populations. However, validation of age estimates requires known-age fish, which are often lacking. We used known-age (ages 1–25) muskellunge (Esox masquinongy) to determine the precision and accuracy of age estimates from fin rays. We also determined whether fin location (anal or pelvic), fin ray number, and preparation methods affected accuracy and precision. Lastly, we determined whether von Bertalanffy growth parameters estimated from fin ray ages were similar to parameters estimated from known ages. Precision and accuracy of age estimates from anal and pelvic rays were similar and estimates were relatively precise (coefficient of variation = 8.5%) and accurate (mean absolute difference from known age = 0.85 years) for ages 4–15, but ages were overestimated for younger fish and underestimated for older fish. Growth models based on estimated age were similar to models based on known age. Anal and pelvic rays offer a nonlethal alternative for age estimation of muskellunge ages 4–15 and for producing reliable estimates of growth.
","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjfas-2018-0404","usgsCitation":"Crane, D.P., Cornett, M.R., Bauerlien, C.J., Hawkins, M.L., Isermann, D.A., Hansbarger, J., Kapuscinski, K., Meerbeek, J., Simonson, T., and Kampa, J.M., 2020, Validity of age estimates from muskellunge (Esox masquinongy) fin rays and associated effects on estimates of growth: Canadian Journal of Fisheries and Aquatic Sciences, v. 77, no. 1, p. 69-80, https://doi.org/10.1139/cjfas-2018-0404.","productDescription":"12 p.","startPage":"69","endPage":"80","ipdsId":"IP-101788","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":501021,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/1807/96798","text":"External Repository"},{"id":395345,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Illinois, Iowa, 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University","active":true,"usgs":false}],"preferred":false,"id":832998,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Meerbeek, Jonathan R.","contributorId":274444,"corporation":false,"usgs":false,"family":"Meerbeek","given":"Jonathan R.","affiliations":[{"id":39338,"text":"Iowa DNR","active":true,"usgs":false}],"preferred":false,"id":832999,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Simonson, Timothy D.","contributorId":274445,"corporation":false,"usgs":false,"family":"Simonson","given":"Timothy D.","affiliations":[{"id":16117,"text":"Wisconsin DNR","active":true,"usgs":false}],"preferred":false,"id":833000,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Kampa, Jeffrey M.","contributorId":274447,"corporation":false,"usgs":false,"family":"Kampa","given":"Jeffrey","email":"","middleInitial":"M.","affiliations":[{"id":16117,"text":"Wisconsin DNR","active":true,"usgs":false}],"preferred":false,"id":833001,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70204192,"text":"70204192 - 2020 - Trends in biodiversity and habitat quantification tools used for market‐based conservation in the United States","interactions":[],"lastModifiedDate":"2020-02-06T10:46:25","indexId":"70204192","displayToPublicDate":"2019-05-24T12:02:36","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1321,"text":"Conservation Biology","active":true,"publicationSubtype":{"id":10}},"title":"Trends in biodiversity and habitat quantification tools used for market‐based conservation in the United States","docAbstract":"Market-based conservation mechanisms are designed to facilitate conservation and mitigation actions for habitat and biodiversity. Their potential is partly hindered, however, by issues surrounding the quantification tools used to assess habitat quality and functionality. Specifically, a lack of transparency and standardization in tool development and gaps in tool availability are cited concerns. To address these issues, we collected information about tools used in United States conservation mechanisms such as eco-label and payments for ecosystem services (PES) programs, conservation banking, and habitat exchanges. We summarized information about tools and explored trends among and within mechanisms using criteria detailing geographic, ecological, and technical features of tools. We identified 69 tools that assessed at least 34 species and 39 habitat types. Where tools reported pricing, 98% were freely available. Most tools required a moderate or greater level of user skill. More tools were applied to states along the west coast of the United States than elsewhere and the level of tool transferability varied markedly among mechanisms. Tools most often incorporated conditions at numerous spatial scales, frequently addressed multiple risks to site viability, and required from 1 to 83 data inputs. Finally, average tool complexity estimates were similar among all mechanisms except PES programs. Our results illustrate the diversity among tools in their ecological features, data needs, and geographic application, supporting concerns about a lack of standardization. However, consistency among tools in user skill requirements, the incorporation of multiple spatial scales, and complexity highlight important commonalities that could serve as a starting point for establishing more standardized tool development and feature incorporation processes. Greater standardization in tool design may not only expand market participation, but may also facilitate a needed assessment of the effectiveness of market-based conservation.","language":"English","publisher":"Wiley","doi":"10.1111/cobi.13349","usgsCitation":"Chiavacci, S.J., and Pindilli, E., 2020, Trends in biodiversity and habitat quantification tools used for market‐based conservation in the United States: Conservation Biology, v. 34, no. 1, p. 125-136, https://doi.org/10.1111/cobi.13349.","productDescription":"12 p.","startPage":"125","endPage":"136","ipdsId":"IP-100463","costCenters":[{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true}],"links":[{"id":458757,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/cobi.13349","text":"Publisher Index Page"},{"id":365465,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"34","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2019-07-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Chiavacci, Scott J. 0000-0003-3579-8377","orcid":"https://orcid.org/0000-0003-3579-8377","contributorId":206161,"corporation":false,"usgs":true,"family":"Chiavacci","given":"Scott","email":"","middleInitial":"J.","affiliations":[{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true}],"preferred":true,"id":765938,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pindilli, Emily 0000-0002-5101-1266 epindilli@usgs.gov","orcid":"https://orcid.org/0000-0002-5101-1266","contributorId":140262,"corporation":false,"usgs":true,"family":"Pindilli","given":"Emily","email":"epindilli@usgs.gov","affiliations":[{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true}],"preferred":true,"id":765939,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70222620,"text":"70222620 - 2020 - Kinematic rupture modeling of ground motion from the M7 Kumamoto, Japan earthquake","interactions":[],"lastModifiedDate":"2021-08-09T13:06:50.0225","indexId":"70222620","displayToPublicDate":"2019-05-22T08:04:51","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3208,"text":"Pure and Applied Geophysics","active":true,"publicationSubtype":{"id":10}},"title":"Kinematic rupture modeling of ground motion from the M7 Kumamoto, Japan earthquake","docAbstract":"We analyzed a kinematic earthquake rupture generator that combines the randomized spatial field approach of Graves and Pitarka (Bull Seismol Soc Am 106:2136–2153, 2016) (GP2016) with the multiple asperity characterization approach of Irikura and Miyake (Pure Appl Geophys 168:85–104, 2011) (IM2011, also known as Irikura recipe). The rupture generator uses a multi-scale hybrid approach that incorporates distinct features of both original approaches, such as small-scale stochastic rupture variability and depth-dependent scaling of rupture speed and slip rate, inherited from GP2016, and specification of discrete high slip rupture patches, inherited from IM2011. The performance of the proposed method is examined in simulations of broadband ground motion from the 2016 Kumamoto, Japan earthquake, as well as comparisons with ground motion prediction equations (GMPEs). We generated rupture models with multi-scale heterogeneity, including a hybrid one in which the slip is a combination of high- slip patches and stochastic small scale variations. We find that the ground motions simulated with these rupture models match the general characteristics of the recorded near-fault motion equally well, over a broad frequency range (0–10 Hz). Additionally, the simulated ground motion is in good agreement with the predictions from Ground Motion Prediction Equations (GMPEs). Nonetheless, due to sensitivity of the ground motion to the local fault rupture characteristics, the performance among the models at near-fault sites is slightly different, with the hybrid model producing a somewhat better fit to the recorded ground velocity waveforms. Sensitivity tests of simulated near-fault ground motion to variations in the prescribed kinematic rupture parameters show that average rupture speeds higher than the default value in GP2016 (average rupture speed = 80% of local shear wave speed), as well as slip rate durations shorter than the default value in GP2016 (rise time coefficient = 1.6), generate ground motions that are higher than the recorded ones at periods longer than 1 s. We found that these two parameters also affect the along strike and updip rupture directivity effects, as illustrated in comparisons with the Kumamoto observations.
In 1988, an important publication moved model calibration and forecasting beyond case studies and theoretical analysis. It reported on a somewhat idyllic graduate student modeling exercise where many of the system properties were known; the primary forecasts of interest were heads in pumping wells after a river was modified. The model was calibrated using manual trial‐and‐error approaches where a model's forecast quality was not related to how well it was calibrated. Here, we investigate whether tools widely available today obviate the shortcomings identified 30 years ago. A reconstructed version of the 1988 true model was tested using increasing parameter estimation sophistication. The parameter estimation demonstrated the inverse problem was non‐unique because only head data were available for calibration. When a flux observation was included, current parameter estimation approaches were able to overcome all calibration and forecast issues noted in 1988. The best forecasts were obtained from a highly parameterized model that used pilot points for hydraulic conductivity and was constrained with soft knowledge. Like the 1988 results, however, the best calibrated model did not produce the best forecasts due to parameter overfitting. Finally, a computationally frugal linear uncertainty analysis demonstrated that the single‐zone model was oversimplified, with only half of the forecasts falling within the calculated uncertainty bounds. Uncertainties from the highly parameterized models had all six forecasts within the calculated uncertainty. The current results outperformed those of the 1988 effort, demonstrating the value of quantitative parameter estimation and uncertainty analysis methods.
Although feathers are commonly used to monitor mercury (Hg) in avian populations, their reliability as a sampling matrix has not been thoroughly assessed for many avian species, including most songbirds (Order Passeriformes). To better understand relationships between total Hg (THg) concentrations in feathers and other tissues for birds in the thrush and sparrow families, we (1) examined variation in THg concentrations among tissues, including feathers from six different tracts, nails, liver, and muscle; (2) tested relationships between THg concentrations in the various feather tracts and those in internal tissues from the same birds, to assess the predictive power of feather THg, and; (3) compared these relationships to those between THg concentrations in nails and internal tissues, to assess the viability of nails as a non-lethal sampling alternative. THg concentrations in all feather tracts and nails were consistently higher than those in the liver and muscle, and THg was higher in the thrushes than the sparrows. When comparing feather tracts, we observed high variation within some individuals, suggesting that estimates of Hg exposure could vary depending on which feather was sampled. Despite this variation, feather type had little effect on the predictive power of feather THg concentrations, which ranged from extremely weak in the sparrows (0.09 ≤ R2 ≤ 0.16) to moderate (0.29 ≤ R2 ≤ 0.42) in the thrushes. Alternatively, we found that nail samples better predicted internal tissue THg concentrations in both the thrushes (0.44 ≤ R2 ≤ 0.48) and sparrows (0.70 ≤ R2 ≤ 0.78). Nails have been used to monitor Hg in mammals and reptiles, but their reliability as a sampling matrix for monitoring Hg in avian populations has yet to be assessed for most taxa. While nails exhibit stronger relationships to internal tissue THg concentrations, they may not be an effective sampling option for all avian species because the collection of sizable nail samples could harm living birds, particularly small songbirds. However, this method may be reasonable for retrospective museum studies. Overall, our results suggest that, despite their current use in the literature, feathers are not a suitable sampling matrix for Hg monitoring in some songbird species.
","language":"English","publisher":"Springer","doi":"10.1007/s10646-019-02052-y","usgsCitation":"Low, K.E., Ramsden, D.K., Jackson, A., Emery, C., Robinson, W.D., Randolph, J., and Eagles-Smith, C.A., 2020, Songbird feathers as indicators of mercury exposure: High variability and low predictive power suggest limitations: Ecotoxicology, v. 29, p. 1281-1292, https://doi.org/10.1007/s10646-019-02052-y.","productDescription":"12 p.","startPage":"1281","endPage":"1292","ipdsId":"IP-096266","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":437226,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9C2S6DQ","text":"USGS data release","linkHelpText":"Mercury concentrations in songbird feathers and tissues"},{"id":365328,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"29","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2019-05-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Low, Katherine E.","contributorId":215868,"corporation":false,"usgs":false,"family":"Low","given":"Katherine","email":"","middleInitial":"E.","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":765584,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ramsden, Danielle K.","contributorId":216803,"corporation":false,"usgs":false,"family":"Ramsden","given":"Danielle","email":"","middleInitial":"K.","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":765585,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jackson, Allyson K.","contributorId":156248,"corporation":false,"usgs":false,"family":"Jackson","given":"Allyson K.","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":765586,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Emery, Colleen 0000-0002-1208-3224","orcid":"https://orcid.org/0000-0002-1208-3224","contributorId":215534,"corporation":false,"usgs":true,"family":"Emery","given":"Colleen","email":"","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":765587,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Robinson, W. Douglas","contributorId":215870,"corporation":false,"usgs":false,"family":"Robinson","given":"W.","email":"","middleInitial":"Douglas","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":765588,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Randolph, Jim","contributorId":215871,"corporation":false,"usgs":false,"family":"Randolph","given":"Jim","email":"","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":765589,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Eagles-Smith, Collin A. 0000-0003-1329-5285 ceagles-smith@usgs.gov","orcid":"https://orcid.org/0000-0003-1329-5285","contributorId":505,"corporation":false,"usgs":true,"family":"Eagles-Smith","given":"Collin","email":"ceagles-smith@usgs.gov","middleInitial":"A.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true},{"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":765583,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70203907,"text":"70203907 - 2020 - Advances in computational morphodynamics using the International River Interface Cooperative (iRIC) software","interactions":[],"lastModifiedDate":"2020-02-06T10:39:11","indexId":"70203907","displayToPublicDate":"2019-05-20T13:54:38","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1425,"text":"Earth Surface Processes and Landforms","active":true,"publicationSubtype":{"id":10}},"title":"Advances in computational morphodynamics using the International River Interface Cooperative (iRIC) software","docAbstract":"Results from computational morphodynamics modeling of coupled flow-bed-sediment systems are described for ten applications as a review of recent advances in the field. Each of these applications is drawn from solvers included in the public-domain International River Interface Cooperative (iRIC) software package. For mesoscale river features such as bars, predictions of alternate and higher mode river bars are shown for flows with equilibrium sediment supply and for a single case of oversupplied sediment. For microscale bed features such as bedforms, computational results are shown for the development and evolution of two-dimensional bedforms using a simple closure-based two-dimensional model, for two- and three-dimensional ripples and dunes using a three-dimensional large-eddy simulation flow model coupled to a physics-based particle transport model, and for the development of bed streaks using a three-dimensional unsteady Reynolds-averaged Navier-Stokes solver with a simple sediment-transport treatment. Finally, macroscale or channel evolution treatments are used to examine the temporal development of meandering channels, a failure model for cantilevered banks, the effect of bank vegetation on channel width, the development of channel networks in tidal systems, and the evolution of bedrock channels. In all examples, computational morphodynamics results from iRIC solvers are shown to compare well to observations of natural bed morphology. For each of the three scales investigated here, brief suggestions for future work and potential research directions are offered.","language":"English","publisher":"Wiley","doi":"10.1002/esp.4653","usgsCitation":"Shimizu, Y., and Nelson, J.M., 2020, Advances in computational morphodynamics using the International River Interface Cooperative (iRIC) software: Earth Surface Processes and Landforms, v. 45, no. 1, p. 11-37, https://doi.org/10.1002/esp.4653.","productDescription":"27 p.","startPage":"11","endPage":"37","ipdsId":"IP-102150","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":467309,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/esp.4653","text":"Publisher Index Page"},{"id":364844,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":364841,"type":{"id":15,"text":"Index Page"},"url":"https://doi.org/10.1002/esp.4653"}],"volume":"45","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2019-07-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Shimizu, Yasuyuki","contributorId":173790,"corporation":false,"usgs":false,"family":"Shimizu","given":"Yasuyuki","email":"","affiliations":[{"id":17805,"text":"Hokkaido University, Sapporo, Japan","active":true,"usgs":false}],"preferred":false,"id":764699,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nelson, Jonathan M. 0000-0002-7632-8526 jmn@usgs.gov","orcid":"https://orcid.org/0000-0002-7632-8526","contributorId":2812,"corporation":false,"usgs":true,"family":"Nelson","given":"Jonathan","email":"jmn@usgs.gov","middleInitial":"M.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":764698,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70203621,"text":"70203621 - 2020 - Ecosystem processes, landcover, climate, and human settlement shape dynamic distributions for golden eagle across the western US","interactions":[],"lastModifiedDate":"2020-02-07T06:35:42","indexId":"70203621","displayToPublicDate":"2019-05-15T08:39:25","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":774,"text":"Animal Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Ecosystem processes, landcover, climate, and human settlement shape dynamic distributions for golden eagle across the western US","docAbstract":"Species–environment relationships for highly mobile species outside of the breeding season are often highly dynamic in response to the collective effects of ever‐changing climatic conditions, food resources, and anthropogenic disturbance. Capturing dynamic space‐use patterns in a model‐based framework is critical as model inference often drives place‐based conservation planning. We applied dynamic occupancy models to broad‐scale golden eagle Aquila chrysaetos survey data collected annually from 2006 to 2012 during the late summer post‐fledging period in the western US. We defined survey sites as 10 km transect segments with a 1 km buffer on either transect side (n = 3540). Derived estimates of occupancy were low (4.4–7.9%) and turnover rates – the probability that occupied sites were newly occupied – were high (88–94%), demonstrating that annual transiency in occupancy dominates late summer behavior for golden eagles. Despite low philopatry during late summer, variation in golden eagle occupancy could be explained by a suite of land cover and annual‐varying covariates including gross primary productivity, drought severity, and human disturbance. Our summary of 13 years of predicted occupancy by golden eagles across the western United States identified areas that are consistently used and that may contribute significantly to golden eagle conservation. Restricting development and targeting mitigation efforts in these areas offers practitioners a framework for conservation prioritization.
","language":"English","publisher":"Zoological Society of London","doi":"10.1111/acv.12511","usgsCitation":"Tack, J.D., Noon, B., Bowen, Z.H., and Fedy, B., 2020, Ecosystem processes, landcover, climate, and human settlement shape dynamic distributions for golden eagle across the western US: Animal Conservation, v. 23, no. 1, p. 72-82, https://doi.org/10.1111/acv.12511.","productDescription":"11 p.","startPage":"72","endPage":"82","ipdsId":"IP-087715","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":458768,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/acv.12511","text":"Publisher Index Page"},{"id":364168,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, California, Colorado, Idaho, Montana, New Mexico, Nebraska, Nevada, North Dakota, Oregon, South Dakota, Utah, Washington, Wyoming","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"MultiPolygon\",\"coordinates\":[[[[-96.443408,42.489495],[-96.079915,41.757895],[-96.089714,41.531778],[-95.871489,41.295797],[-95.885349,40.721093],[-95.336242,40.019104],[-102.051744,40.003078],[-102.04192,37.035083],[-102.979613,36.998549],[-103.002247,36.911587],[-103.064423,32.000518],[-106.565142,32.000736],[-106.577244,31.810406],[-106.750547,31.783706],[-108.208394,31.783599],[-108.208573,31.333395],[-111.000643,31.332177],[-114.813613,32.494277],[-114.722746,32.713071],[-117.118868,32.534706],[-117.50565,33.334063],[-118.088896,33.729817],[-118.428407,33.774715],[-118.519514,34.027509],[-119.159554,34.119653],[-119.616862,34.420995],[-120.441975,34.451512],[-120.608355,34.556656],[-120.644311,35.139616],[-120.873046,35.225688],[-120.884757,35.430196],[-121.851967,36.277831],[-121.932508,36.559935],[-121.788278,36.803994],[-121.880167,36.950151],[-122.140578,36.97495],[-122.419113,37.24147],[-122.511983,37.77113],[-122.425942,37.810979],[-122.168449,37.504143],[-122.144396,37.581866],[-122.385908,37.908136],[-122.301804,38.105142],[-122.484411,38.11496],[-122.492474,37.82484],[-122.972378,38.020247],[-123.103706,38.415541],[-123.725367,38.917438],[-123.851714,39.832041],[-124.373599,40.392923],[-124.063076,41.439579],[-124.536073,42.814175],[-124.150267,43.91085],[-123.962887,45.280218],[-123.996766,46.20399],[-123.548194,46.248245],[-124.029924,46.308312],[-124.06842,46.601397],[-123.97083,46.47537],[-123.84621,46.716795],[-124.022413,46.708973],[-124.108078,46.836388],[-123.86018,46.948556],[-124.138035,46.970959],[-124.425195,47.738434],[-124.672427,47.964414],[-124.727022,48.371101],[-123.981032,48.164761],[-122.748911,48.117026],[-122.637425,47.889945],[-123.15598,47.355745],[-122.527593,47.905882],[-122.578211,47.254804],[-122.725738,47.33047],[-122.691771,47.141958],[-122.796646,47.341654],[-122.863732,47.270221],[-122.67813,47.103866],[-122.364168,47.335953],[-122.429841,47.658919],[-122.230046,47.970917],[-122.425572,48.232887],[-122.358375,48.056133],[-122.512031,48.133931],[-122.424102,48.334346],[-122.689121,48.476849],[-122.425271,48.599522],[-122.796887,48.975026],[-97.229039,49.000687],[-97.116185,48.709348],[-97.145243,48.174046],[-96.854812,47.606328],[-96.774763,46.607461],[-96.557952,46.102442],[-96.612512,45.794442],[-96.82616,45.654164],[-96.452315,45.208986],[-96.453049,43.500415],[-96.591213,43.500514],[-96.439335,43.113916],[-96.630311,42.770885],[-96.443408,42.489495]]],[[[-119.789798,34.05726],[-119.5667,34.053452],[-119.795938,33.962929],[-119.916216,34.058351],[-119.789798,34.05726]]],[[[-118.524531,32.895488],[-118.573522,32.969183],[-118.369984,32.839273],[-118.524531,32.895488]]],[[[-118.500212,33.449592],[-118.32446,33.348782],[-118.593969,33.467198],[-118.500212,33.449592]]],[[[-122.519535,48.288314],[-122.66921,48.240614],[-122.400628,48.036563],[-122.419274,47.912125],[-122.744612,48.20965],[-122.664928,48.374823],[-122.519535,48.288314]]],[[[-122.800217,48.60169],[-122.883759,48.418793],[-123.173061,48.579086],[-122.949116,48.693398],[-122.743049,48.661991],[-122.800217,48.60169]]]]},\"properties\":{\"name\":\"Arizona\",\"nation\":\"USA \"}}]}","volume":"23","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2019-05-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Tack, J. D.","contributorId":222253,"corporation":false,"usgs":false,"family":"Tack","given":"J.","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":781683,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Noon, B.R.","contributorId":24311,"corporation":false,"usgs":true,"family":"Noon","given":"B.R.","email":"","affiliations":[],"preferred":false,"id":781684,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bowen, Zachary H. 0000-0002-8656-1831 bowenz@usgs.gov","orcid":"https://orcid.org/0000-0002-8656-1831","contributorId":821,"corporation":false,"usgs":true,"family":"Bowen","given":"Zachary","email":"bowenz@usgs.gov","middleInitial":"H.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":763301,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fedy, B.C.","contributorId":35427,"corporation":false,"usgs":true,"family":"Fedy","given":"B.C.","email":"","affiliations":[],"preferred":false,"id":781685,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70209712,"text":"70209712 - 2020 - Assessment experimental semivariogram uncertainty in the presence of a polynomial drift","interactions":[],"lastModifiedDate":"2020-04-27T12:23:13.834768","indexId":"70209712","displayToPublicDate":"2019-05-14T09:54:49","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2832,"text":"Natural Resources Research","onlineIssn":"1573-8981","printIssn":"1520-7439","active":true,"publicationSubtype":{"id":10}},"title":"Assessment experimental semivariogram uncertainty in the presence of a polynomial drift","docAbstract":"The semivariogram, which measures the spatial variability between experimental data, is generally used as a structural input in all two-point geostatistical procedures. However, in most geoscience applications, experimental semivariograms are usually computed from a limited number of sparsely spaced measurements, which results in uncertainty associated with the semivariance values estimated for a specified number of lags. More importantly, considering a spatial variable modelled by a nonstationary random field, uncertainty is not only in the experimental semivariogram of the residuals, but also in the coefficients of the drift model estimated from the available experimental data. Therefore, when assessing the reliability of an experimental semivariogram (or estimated semivariances) in the nonstationary case, both aforementioned uncertainties should be taken into account. The aim of this paper is to extend the “Generalised Bootstrap” procedure to the nonstationary model by propagating the uncertainty associated with the estimated drift coefficients into the uncertainty in the experimental semivariogram of the residuals. The proposed methodology is demonstrated in a case study using abundant geophysical measurements characterised by a nonstationary random function. Two scenarios are evaluated in the case study: (1) it is assumed that the drift coefficients can be estimated without any uncertainty, and (2) uncertainty of the drift coefficients is taken into account. We have explained the methodology that allows to assess the uncertainty of the semivariogram lag estimates in the presence of the drift in the mean. Considering the second scenario, uncertainty is obviously larger than the case where uncertainty of the drift in the mean is ignored. This evaluation should be considered in applications where the data is often rather limited, such as subsurface hydrology (i.e. porosity, transmissivity), soil science (i.e. heavy metal content, soil moisture) and mining (i.e. scoping or pre-feasibility stage of the project). In fact, modern geostatistics should provide not only the semivariogram estimates but also estimation of its uncertainty.","language":"English","publisher":"Springer","doi":"10.1007/s11053-019-09496-3","collaboration":"","usgsCitation":"Oktay, E., Pardo-Iguzquiza, E., and Olea, R.A., 2020, Assessment experimental semivariogram uncertainty in the presence of a polynomial drift: Natural Resources Research, v. 29, no. 2, p. 1087-1099, https://doi.org/10.1007/s11053-019-09496-3.","productDescription":"13 p.","startPage":"1087","endPage":"1099","ipdsId":"IP-087621","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":374190,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"29","issue":"2","noUsgsAuthors":false,"publicationDate":"2019-05-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Oktay, Erten","contributorId":224283,"corporation":false,"usgs":false,"family":"Oktay","given":"Erten","email":"","affiliations":[{"id":40846,"text":"Curtin U. Australia","active":true,"usgs":false}],"preferred":false,"id":787635,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pardo-Iguzquiza, Eulogio","contributorId":208073,"corporation":false,"usgs":false,"family":"Pardo-Iguzquiza","given":"Eulogio","email":"","affiliations":[{"id":40847,"text":"Instituto Geologico y Minero de Espana","active":true,"usgs":false}],"preferred":false,"id":787636,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Olea, Ricardo A. 0000-0003-4308-0808 rolea@usgs.gov","orcid":"https://orcid.org/0000-0003-4308-0808","contributorId":208109,"corporation":false,"usgs":true,"family":"Olea","given":"Ricardo","email":"rolea@usgs.gov","middleInitial":"A.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":787637,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ]}