The 72‐km‐long Teton fault in northwestern Wyoming is an ideal candidate for reconstructing the lateral extent of surface‐rupturing earthquakes and testing models of normal‐fault segmentation. To explore the history of earthquakes on the northern Teton fault, we hand‐excavated two trenches at the Steamboat Mountain site, where the east‐dipping Teton fault has vertically displaced west‐sloping alluvial‐fan surfaces. The trenches exposed glaciofluvial, alluvial‐fan, and scarp‐derived colluvial sediments and stratigraphic and structural evidence of two surface‐rupturing earthquakes (SM1 and SM2). A Bayesian geochronologic model for the site includes three optically stimulated luminescence ages (∼12–17 ka) for the glaciofluvial units and 16 radiocarbon ages (∼1.2–8.6 ka) for the alluvial‐fan and colluvial units and constrains SM1 and SM2 to 5.5±0.2 ka, 1σ (5.2–5.9 ka, 95%) and 9.7±0.9 ka, 1σ (8.5–11.5 ka, 95%), respectively. Structural, stratigraphic, and geomorphic relations yield vertical displacements for SM1 (2.0±0.6 m, 1σ) and SM2 (2.0±1.0 m, 1σ). The Steamboat Mountain paleoseismic chronology overlaps temporally with earthquakes interpreted from previous terrestrial and lacustrine paleoseismic data along the fault. Integrating these data, we infer that the youngest Teton fault rupture occurred at ∼5.3 ka, generated 1.7±1.0 m, 1σ of vertical displacement along 51–70 km of the fault, and had a moment magnitude (Mw) of ∼7.0–7.2. This rupture was apparently unimpeded by structural complexities along the Teton fault. The integrated chronology permits a previous full‐length rupture at ∼10 ka and possible partial ruptures of the fault at ∼8–9 ka. To reconcile conflicting terrestrial and lacustrine paleoseismic data, we propose a hypothesis of alternating full‐ and partial‐length ruptures of the Teton fault, including Mw∼6.5–7.2 earthquakes every ∼1.2 ky. Additional paleoseismic data for the northern and central sections of the fault would serve to test this bimodal rupture hypothesis.
Rangelands cover 70% of the world's land surface, and provide critical ecosystem services of primary production, soil carbon storage, and nutrient cycling. These ecosystem services are governed by very fine-scale spatial patterning of soil carbon, nutrients, and plant species at the centimeter-to-meter scales, a phenomenon known as “islands of fertility”. Such fine-scale dynamics are challenging to detect with most satellite and manned airborne platforms. Remote sensing from unmanned aerial vehicles (UAVs) provides an alternative option for detecting fine-scale soil nutrient and plant species changes in rangelands tn0020 smaller extents. We demonstrate that a model incorporating the fusion of UAV multispectral and structure-from-motion photogrammetry classifies plant functional types and bare soil cover with an overall accuracy of 95% in rangelands degraded by shrub encroachment and disturbed by fire. We further demonstrate that employing UAV hyperspectral and LiDAR fusion greatly improves upon these results by classifying 9 different plant species and soil fertility microsite types (SFMT) with an overall accuracy of 87%. Among them, creosote bush and black grama, the most important native species in the rangeland, have the highest producer's accuracies at 98% and 94%, respectively. The integration of UAV LiDAR-derived plant height differences was critical in these improvements. Finally, we use synthesis of the UAV datasets with ground-based LiDAR surveys and lab characterization of soils to estimate that the burned rangeland potentially lost 1474 kg/ha of C and 113 kg/ha of N owing to soil erosion processes during the first year after a prescribed fire. However, during the second-year post-fire, grass and plant-interspace SFMT functioned as net sinks for sediment and nutrients and gained approximately 175 kg/ha C and 14 kg/ha N, combined. These results provide important site-specific insight that is relevant to the 423 Mha of grasslands and shrublands that are burned globally each year. While fire, and specifically post-fire erosion, can degrade some rangelands, post-fire plant-soil-nutrient dynamics might provide a competitive advantage to grasses in rangelands degraded by shrub encroachment. These novel UAV and ground-based LiDAR remote sensing approaches thus provide important details towards more accurate accounting of the carbon and nutrients in the soil surface of rangelands.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.rse.2020.112223","usgsCitation":"Sankey, J.B., Sankey, T.T., Li, J., Ravi, S., Wang, G., Caster, J., and Kasprak, A., 2021, Quantifying plant-soil-nutrient dynamics in rangelands: Fusion of UAV hyperspectral-LiDAR, UAV multispectral-photogrammetry, and ground-based LiDAR-digital photography in a shrub-encroached desert grassland: Remote Sensing of Environment, v. 253, 112223, 18 p., https://doi.org/10.1016/j.rse.2020.112223.","productDescription":"112223, 18 p.","ipdsId":"IP-110017","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":454141,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.rse.2020.112223","text":"Publisher Index Page"},{"id":381413,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Mexico","otherGeospatial":"Sevilleta National Wildlife Refuge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -106.80770874023438,\n 34.301471780404476\n ],\n [\n -106.63192749023438,\n 34.301471780404476\n ],\n [\n -106.63192749023438,\n 34.412574601595\n ],\n [\n -106.80770874023438,\n 34.412574601595\n ],\n [\n -106.80770874023438,\n 34.301471780404476\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"253","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Sankey, Joel B. 0000-0003-3150-4992 jsankey@usgs.gov","orcid":"https://orcid.org/0000-0003-3150-4992","contributorId":3935,"corporation":false,"usgs":true,"family":"Sankey","given":"Joel","email":"jsankey@usgs.gov","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":806945,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sankey, Temuulen T.","contributorId":173297,"corporation":false,"usgs":false,"family":"Sankey","given":"Temuulen","email":"","middleInitial":"T.","affiliations":[{"id":7202,"text":"NAU","active":true,"usgs":false}],"preferred":false,"id":806946,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Li, Junran","contributorId":202740,"corporation":false,"usgs":false,"family":"Li","given":"Junran","email":"","affiliations":[{"id":36521,"text":"Department of Geosciences, University of Tulsa","active":true,"usgs":false}],"preferred":false,"id":806947,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ravi, Sujith","contributorId":202738,"corporation":false,"usgs":false,"family":"Ravi","given":"Sujith","email":"","affiliations":[{"id":36520,"text":"Department of Earth and Environmental Science, Temple University","active":true,"usgs":false}],"preferred":false,"id":806948,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wang, Guan","contributorId":202741,"corporation":false,"usgs":false,"family":"Wang","given":"Guan","email":"","affiliations":[{"id":36521,"text":"Department of Geosciences, University of Tulsa","active":true,"usgs":false}],"preferred":false,"id":806949,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Caster, Joshua 0000-0002-2858-1228 jcaster@usgs.gov","orcid":"https://orcid.org/0000-0002-2858-1228","contributorId":199033,"corporation":false,"usgs":true,"family":"Caster","given":"Joshua","email":"jcaster@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":806950,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kasprak, Alan 0000-0001-8184-6128","orcid":"https://orcid.org/0000-0001-8184-6128","contributorId":245742,"corporation":false,"usgs":false,"family":"Kasprak","given":"Alan","affiliations":[{"id":49307,"text":"Current: Utah State University. Former: Southwest Biological Science Center, Grand Canyon Monitoring and Research Center, U.S. Geological Survey, Flagstaff, AZ 86001, USA","active":true,"usgs":false}],"preferred":false,"id":806951,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70219508,"text":"70219508 - 2021 - Expert assessment of future vulnerability of the global peatland carbon sink","interactions":[],"lastModifiedDate":"2021-04-12T19:54:42.096571","indexId":"70219508","displayToPublicDate":"2020-12-07T10:48:43","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2841,"text":"Nature Climate Change","onlineIssn":"1758-6798","printIssn":"1758-678X","active":true,"publicationSubtype":{"id":10}},"title":"Expert assessment of future vulnerability of the global peatland carbon sink","docAbstract":"The carbon balance of peatlands is predicted to shift from a sink to a source this century. However, peatland ecosystems are still omitted from the main Earth system models that are used for future climate change projections, and they are not considered in integrated assessment models that are used in impact and mitigation studies. By using evidence synthesized from the literature and an expert elicitation, we define and quantify the leading drivers of change that have impacted peatland carbon stocks during the Holocene and predict their effect during this century and in the far future. We also identify uncertainties and knowledge gaps in the scientific community and provide insight towards better integration of peatlands into modelling frameworks. Given the importance of the contribution by peatlands to the global carbon cycle, this study shows that peatland science is a critical research area and that we still have a long way to go to fully understand the peatland–carbon–climate nexus.
","language":"English","publisher":"Nature","doi":"10.1038/s41558-020-00944-0","usgsCitation":"Loisel, J., Gallego-Sala, A., Amesbury, M., Magnan, G., Anshari, G., Beilman, D., Blewett, J., Benevides, J.C., Camill, P., Charman, D., Chawchai, S., Hedgpeth, A., Kleinen, T., Korhola, A., Large, D., Muller, J., Mansilla, C., van Bellen, S., West, J.B., Yu, Z., Bubier, J., Garneau, M., Moore, T., Sannel, A.B., Väliranta, M., Page, S., Bechtold, M., Brovkin, V., Cole, L.E., Chanton, J., Christensen, T.R., Davies, M.A., De Vleeschouwer, F., Finkelstein, S., Frolking, S., Galka, M., Gandois, L., Girkin, N., Harris, .., Heinemeyer, A., Hoyt, A., Jones, M.C., Joos, F., Juutinen, S., Kaiser, K., Lamentowicz, M., Larmola, T., Leifeld, M., Lohila, A., Milner, A., Minkkinen, K., Moss, P., Naafs, B., Nichols, J., O'Donnell, J., Payne, R., Philben, M., Pilo, S., Quillet, A., Ratnayake, A., Roland, T., Sjogersten, S., Sonnentag, O., Swindles, G., Swinnen, W., Talbott, J., Treat, C., Valach, A., and Wu, J., 2021, Expert assessment of future vulnerability of the global peatland carbon sink: Nature Climate Change, v. 11, p. 70-77, https://doi.org/10.1038/s41558-020-00944-0.","productDescription":"8 p.","startPage":"70","endPage":"77","ipdsId":"IP-112925","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":467262,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1038/s41558-020-00944-0","text":"External Repository"},{"id":385029,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11","noUsgsAuthors":false,"publicationDate":"2020-12-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Loisel, Julie","contributorId":166672,"corporation":false,"usgs":false,"family":"Loisel","given":"Julie","email":"","affiliations":[{"id":18162,"text":"University of Helsinki","active":true,"usgs":false}],"preferred":false,"id":813835,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gallego-Sala, A.V.","contributorId":257233,"corporation":false,"usgs":false,"family":"Gallego-Sala","given":"A.V.","email":"","affiliations":[{"id":17840,"text":"University of Exeter","active":true,"usgs":false}],"preferred":false,"id":813836,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Amesbury, M.J.","contributorId":257234,"corporation":false,"usgs":false,"family":"Amesbury","given":"M.J.","affiliations":[{"id":17840,"text":"University of Exeter","active":true,"usgs":false}],"preferred":false,"id":813837,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Magnan, G.","contributorId":257272,"corporation":false,"usgs":false,"family":"Magnan","given":"G.","email":"","affiliations":[],"preferred":false,"id":813959,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Anshari, G.","contributorId":257273,"corporation":false,"usgs":false,"family":"Anshari","given":"G.","email":"","affiliations":[],"preferred":false,"id":813960,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Beilman, D. W.","contributorId":257274,"corporation":false,"usgs":false,"family":"Beilman","given":"D. W.","affiliations":[],"preferred":false,"id":813961,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Blewett, J.","contributorId":257276,"corporation":false,"usgs":false,"family":"Blewett","given":"J.","email":"","affiliations":[],"preferred":false,"id":813962,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Benevides, J. C.","contributorId":257275,"corporation":false,"usgs":false,"family":"Benevides","given":"J.","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":813963,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Camill, P.","contributorId":257277,"corporation":false,"usgs":false,"family":"Camill","given":"P.","affiliations":[],"preferred":false,"id":813964,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Charman, D. J.","contributorId":257278,"corporation":false,"usgs":false,"family":"Charman","given":"D. J.","affiliations":[],"preferred":false,"id":813965,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Chawchai, S.","contributorId":257279,"corporation":false,"usgs":false,"family":"Chawchai","given":"S.","email":"","affiliations":[],"preferred":false,"id":813966,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Hedgpeth, A.","contributorId":257280,"corporation":false,"usgs":false,"family":"Hedgpeth","given":"A.","email":"","affiliations":[],"preferred":false,"id":813967,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Kleinen, T.","contributorId":257281,"corporation":false,"usgs":false,"family":"Kleinen","given":"T.","affiliations":[],"preferred":false,"id":813968,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Korhola, A.","contributorId":257282,"corporation":false,"usgs":false,"family":"Korhola","given":"A.","affiliations":[],"preferred":false,"id":813969,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Large, D.","contributorId":257283,"corporation":false,"usgs":false,"family":"Large","given":"D.","email":"","affiliations":[],"preferred":false,"id":813970,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Muller, J.","contributorId":257285,"corporation":false,"usgs":false,"family":"Muller","given":"J.","email":"","affiliations":[],"preferred":false,"id":813971,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Mansilla, C. A.","contributorId":257284,"corporation":false,"usgs":false,"family":"Mansilla","given":"C. A.","affiliations":[],"preferred":false,"id":813972,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"van Bellen, S.","contributorId":257286,"corporation":false,"usgs":false,"family":"van Bellen","given":"S.","affiliations":[],"preferred":false,"id":813973,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"West, J. B.","contributorId":13847,"corporation":false,"usgs":false,"family":"West","given":"J.","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":813974,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Yu, Z.","contributorId":32696,"corporation":false,"usgs":true,"family":"Yu","given":"Z.","email":"","affiliations":[],"preferred":false,"id":813975,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Bubier, J. L.","contributorId":91197,"corporation":false,"usgs":false,"family":"Bubier","given":"J. L.","affiliations":[],"preferred":false,"id":813976,"contributorType":{"id":1,"text":"Authors"},"rank":22},{"text":"Garneau, M.","contributorId":166668,"corporation":false,"usgs":false,"family":"Garneau","given":"M.","affiliations":[{"id":24488,"text":"Universite du Quebec a Montreal","active":true,"usgs":false}],"preferred":false,"id":813977,"contributorType":{"id":1,"text":"Authors"},"rank":23},{"text":"Moore, T.","contributorId":257287,"corporation":false,"usgs":false,"family":"Moore","given":"T.","affiliations":[],"preferred":false,"id":813978,"contributorType":{"id":1,"text":"Authors"},"rank":24},{"text":"Sannel, A. B. K.","contributorId":38450,"corporation":false,"usgs":false,"family":"Sannel","given":"A.","email":"","middleInitial":"B. K.","affiliations":[],"preferred":false,"id":813979,"contributorType":{"id":1,"text":"Authors"},"rank":25},{"text":"Väliranta, M.","contributorId":257289,"corporation":false,"usgs":false,"family":"Väliranta","given":"M.","affiliations":[],"preferred":false,"id":813981,"contributorType":{"id":1,"text":"Authors"},"rank":26},{"text":"Page, S.","contributorId":257288,"corporation":false,"usgs":false,"family":"Page","given":"S.","email":"","affiliations":[],"preferred":false,"id":813980,"contributorType":{"id":1,"text":"Authors"},"rank":26},{"text":"Bechtold, M.","contributorId":257290,"corporation":false,"usgs":false,"family":"Bechtold","given":"M.","email":"","affiliations":[],"preferred":false,"id":813982,"contributorType":{"id":1,"text":"Authors"},"rank":27},{"text":"Brovkin, V.","contributorId":94188,"corporation":false,"usgs":false,"family":"Brovkin","given":"V.","affiliations":[],"preferred":false,"id":813983,"contributorType":{"id":1,"text":"Authors"},"rank":28},{"text":"Cole, L. E. S.","contributorId":257291,"corporation":false,"usgs":false,"family":"Cole","given":"L.","email":"","middleInitial":"E. S.","affiliations":[],"preferred":false,"id":813984,"contributorType":{"id":1,"text":"Authors"},"rank":29},{"text":"Chanton, J. P.","contributorId":7429,"corporation":false,"usgs":false,"family":"Chanton","given":"J. P.","affiliations":[],"preferred":false,"id":813985,"contributorType":{"id":1,"text":"Authors"},"rank":30},{"text":"Christensen, T. R.","contributorId":257292,"corporation":false,"usgs":false,"family":"Christensen","given":"T.","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":813986,"contributorType":{"id":1,"text":"Authors"},"rank":31},{"text":"Davies, M. A.","contributorId":53981,"corporation":false,"usgs":false,"family":"Davies","given":"M.","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":813987,"contributorType":{"id":1,"text":"Authors"},"rank":32},{"text":"De Vleeschouwer, F.","contributorId":257295,"corporation":false,"usgs":false,"family":"De Vleeschouwer","given":"F.","affiliations":[],"preferred":false,"id":813993,"contributorType":{"id":1,"text":"Authors"},"rank":33},{"text":"Finkelstein, S.A.","contributorId":257296,"corporation":false,"usgs":false,"family":"Finkelstein","given":"S.A.","email":"","affiliations":[],"preferred":false,"id":813994,"contributorType":{"id":1,"text":"Authors"},"rank":34},{"text":"Frolking, S.","contributorId":96565,"corporation":false,"usgs":true,"family":"Frolking","given":"S.","affiliations":[],"preferred":false,"id":813995,"contributorType":{"id":1,"text":"Authors"},"rank":35},{"text":"Galka, M.","contributorId":257297,"corporation":false,"usgs":false,"family":"Galka","given":"M.","affiliations":[],"preferred":false,"id":813996,"contributorType":{"id":1,"text":"Authors"},"rank":36},{"text":"Gandois, L.","contributorId":257298,"corporation":false,"usgs":false,"family":"Gandois","given":"L.","email":"","affiliations":[],"preferred":false,"id":813997,"contributorType":{"id":1,"text":"Authors"},"rank":37},{"text":"Girkin, N.","contributorId":257299,"corporation":false,"usgs":false,"family":"Girkin","given":"N.","email":"","affiliations":[],"preferred":false,"id":813998,"contributorType":{"id":1,"text":"Authors"},"rank":38},{"text":"Harris, .L.I.","contributorId":257300,"corporation":false,"usgs":false,"family":"Harris","given":".L.I.","affiliations":[],"preferred":false,"id":813999,"contributorType":{"id":1,"text":"Authors"},"rank":39},{"text":"Heinemeyer, A.","contributorId":257301,"corporation":false,"usgs":false,"family":"Heinemeyer","given":"A.","email":"","affiliations":[],"preferred":false,"id":814000,"contributorType":{"id":1,"text":"Authors"},"rank":40},{"text":"Hoyt, A.M.","contributorId":257302,"corporation":false,"usgs":false,"family":"Hoyt","given":"A.M.","email":"","affiliations":[],"preferred":false,"id":814001,"contributorType":{"id":1,"text":"Authors"},"rank":41},{"text":"Jones, Miriam C. 0000-0002-6650-7619 miriamjones@usgs.gov","orcid":"https://orcid.org/0000-0002-6650-7619","contributorId":4056,"corporation":false,"usgs":true,"family":"Jones","given":"Miriam","email":"miriamjones@usgs.gov","middleInitial":"C.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":813838,"contributorType":{"id":1,"text":"Authors"},"rank":42},{"text":"Joos, F.","contributorId":30786,"corporation":false,"usgs":true,"family":"Joos","given":"F.","email":"","affiliations":[],"preferred":false,"id":814002,"contributorType":{"id":1,"text":"Authors"},"rank":43},{"text":"Juutinen, S.","contributorId":257303,"corporation":false,"usgs":false,"family":"Juutinen","given":"S.","affiliations":[],"preferred":false,"id":814003,"contributorType":{"id":1,"text":"Authors"},"rank":44},{"text":"Kaiser, K.","contributorId":33539,"corporation":false,"usgs":true,"family":"Kaiser","given":"K.","email":"","affiliations":[],"preferred":false,"id":814004,"contributorType":{"id":1,"text":"Authors"},"rank":45},{"text":"Lamentowicz, M.","contributorId":257307,"corporation":false,"usgs":false,"family":"Lamentowicz","given":"M.","email":"","affiliations":[],"preferred":false,"id":814006,"contributorType":{"id":1,"text":"Authors"},"rank":46},{"text":"Larmola, T.","contributorId":257305,"corporation":false,"usgs":false,"family":"Larmola","given":"T.","affiliations":[],"preferred":false,"id":814005,"contributorType":{"id":1,"text":"Authors"},"rank":47},{"text":"Leifeld, M.","contributorId":257308,"corporation":false,"usgs":false,"family":"Leifeld","given":"M.","email":"","affiliations":[],"preferred":false,"id":814007,"contributorType":{"id":1,"text":"Authors"},"rank":48},{"text":"Lohila, A.","contributorId":257309,"corporation":false,"usgs":false,"family":"Lohila","given":"A.","affiliations":[],"preferred":false,"id":814008,"contributorType":{"id":1,"text":"Authors"},"rank":49},{"text":"Milner, A.M.","contributorId":95636,"corporation":false,"usgs":true,"family":"Milner","given":"A.M.","email":"","affiliations":[],"preferred":false,"id":814009,"contributorType":{"id":1,"text":"Authors"},"rank":50},{"text":"Minkkinen, Kari","contributorId":169404,"corporation":false,"usgs":false,"family":"Minkkinen","given":"Kari","email":"","affiliations":[{"id":18162,"text":"University of Helsinki","active":true,"usgs":false}],"preferred":false,"id":814010,"contributorType":{"id":1,"text":"Authors"},"rank":51},{"text":"Moss, P.","contributorId":257310,"corporation":false,"usgs":false,"family":"Moss","given":"P.","email":"","affiliations":[],"preferred":false,"id":814011,"contributorType":{"id":1,"text":"Authors"},"rank":52},{"text":"Naafs, B.D.A.","contributorId":257311,"corporation":false,"usgs":false,"family":"Naafs","given":"B.D.A.","email":"","affiliations":[],"preferred":false,"id":814037,"contributorType":{"id":1,"text":"Authors"},"rank":53},{"text":"Nichols, J.","contributorId":257312,"corporation":false,"usgs":false,"family":"Nichols","given":"J.","affiliations":[],"preferred":false,"id":814038,"contributorType":{"id":1,"text":"Authors"},"rank":54},{"text":"O'Donnell, J.","contributorId":34785,"corporation":false,"usgs":true,"family":"O'Donnell","given":"J.","affiliations":[],"preferred":false,"id":814039,"contributorType":{"id":1,"text":"Authors"},"rank":55},{"text":"Payne, R.","contributorId":257313,"corporation":false,"usgs":false,"family":"Payne","given":"R.","email":"","affiliations":[],"preferred":false,"id":814040,"contributorType":{"id":1,"text":"Authors"},"rank":56},{"text":"Philben, M.","contributorId":257314,"corporation":false,"usgs":false,"family":"Philben","given":"M.","email":"","affiliations":[],"preferred":false,"id":814041,"contributorType":{"id":1,"text":"Authors"},"rank":57},{"text":"Pilo, S.","contributorId":257315,"corporation":false,"usgs":false,"family":"Pilo","given":"S.","email":"","affiliations":[],"preferred":false,"id":814042,"contributorType":{"id":1,"text":"Authors"},"rank":58},{"text":"Quillet, A.","contributorId":257316,"corporation":false,"usgs":false,"family":"Quillet","given":"A.","email":"","affiliations":[],"preferred":false,"id":814049,"contributorType":{"id":1,"text":"Authors"},"rank":59},{"text":"Ratnayake, A.S.","contributorId":257318,"corporation":false,"usgs":false,"family":"Ratnayake","given":"A.S.","email":"","affiliations":[],"preferred":false,"id":814050,"contributorType":{"id":1,"text":"Authors"},"rank":60},{"text":"Roland, T.P.","contributorId":257320,"corporation":false,"usgs":false,"family":"Roland","given":"T.P.","email":"","affiliations":[],"preferred":false,"id":814051,"contributorType":{"id":1,"text":"Authors"},"rank":61},{"text":"Sjogersten, S.","contributorId":257321,"corporation":false,"usgs":false,"family":"Sjogersten","given":"S.","email":"","affiliations":[],"preferred":false,"id":814052,"contributorType":{"id":1,"text":"Authors"},"rank":62},{"text":"Sonnentag, O.","contributorId":257322,"corporation":false,"usgs":false,"family":"Sonnentag","given":"O.","affiliations":[],"preferred":false,"id":814053,"contributorType":{"id":1,"text":"Authors"},"rank":63},{"text":"Swindles, G.T.","contributorId":257323,"corporation":false,"usgs":false,"family":"Swindles","given":"G.T.","affiliations":[],"preferred":false,"id":814054,"contributorType":{"id":1,"text":"Authors"},"rank":64},{"text":"Swinnen, W.","contributorId":257324,"corporation":false,"usgs":false,"family":"Swinnen","given":"W.","affiliations":[],"preferred":false,"id":814055,"contributorType":{"id":1,"text":"Authors"},"rank":65},{"text":"Talbott, J.","contributorId":34318,"corporation":false,"usgs":true,"family":"Talbott","given":"J.","email":"","affiliations":[],"preferred":false,"id":814056,"contributorType":{"id":1,"text":"Authors"},"rank":66},{"text":"Treat, C. C.","contributorId":257236,"corporation":false,"usgs":false,"family":"Treat","given":"C. C.","affiliations":[{"id":51984,"text":"University of Finland","active":true,"usgs":false}],"preferred":false,"id":814057,"contributorType":{"id":1,"text":"Authors"},"rank":67},{"text":"Valach, A.C.","contributorId":257325,"corporation":false,"usgs":false,"family":"Valach","given":"A.C.","affiliations":[],"preferred":false,"id":814058,"contributorType":{"id":1,"text":"Authors"},"rank":68},{"text":"Wu, J.","contributorId":56998,"corporation":false,"usgs":true,"family":"Wu","given":"J.","email":"","affiliations":[],"preferred":false,"id":814059,"contributorType":{"id":1,"text":"Authors"},"rank":69}]}} ,{"id":70250892,"text":"70250892 - 2021 - Multi-geophysical parameter classification of the Montserrat geothermal system","interactions":[],"lastModifiedDate":"2024-01-11T14:11:47.485373","indexId":"70250892","displayToPublicDate":"2020-12-05T08:07:40","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1828,"text":"Geothermics","active":true,"publicationSubtype":{"id":10}},"title":"Multi-geophysical parameter classification of the Montserrat geothermal system","docAbstract":"Multi-geophysical parameter classification can help to reduce the uncertainties of interpretations that often rely on one geophysical technique. Integrating these varying datasets requires a more robust classification approach rather than traditional qualitative methods. In this study, we applied the Fuzzy c-means (FCM) method to quantitatively classify similarities in a high resolution seismic tomography, a magnetotellurics and gravity datasets obtained in Montserrat. To group similar datapoints, this application uses a Euclidean distance measure and a membership function. Assigned membership values indicate the degree to which a datapoint belongs to a specific class. The spatial distribution of the derived classes, each classified with distinct geophysical parameters, helped to provide new structural and petrological information of the Montserrat geothermal system. In comparison to previous models, our new cluster model highlights two major improvements. These include the resolution and assessment of the spatial extension and 3D geometry of previously undetected features within the Montserrat geothermal system and the constrain and characterization of earlier identified anomalies. We additionally utilized geological and petrological data obtained from three geothermal wells in the Montserrat geothermal system to help validate our classifications. Based on a semi-quantitative approach we assessed the reliability of the FCM technique in relation to the likely uncertainties of the different geophysical models.
Niche breadth and position can influence diversification among closely related species or populations, yet limited empirical data exist concerning the predictability of the outcomes. We explored the effects of these factors on the evolution of the Emoia atrocostata species group, an insular radiation of lizards in the western Pacific Ocean and Indo-Australasia composed of both endemic and widespread species that differ in niche occupancy. We used molecular data and phylogeographical diffusion models to estimate the timing and patterns of range expansion, and ancestral reconstruction methods to infer shifts in ecology. We show evidence of multidirectional spread from a centre of origin in western Micronesia, and that the phyletic diversity of the group is derived from a putative habitat specialist that survives in the littoral zone. This species is composed of paraphyletic lineages that represent stages or possible endpoints in the continuum toward speciation. Several descendant species have transitioned to either strand or interior forest habitat, but only on remote islands with depauperate terrestrial faunas. Our results suggest that the atrocostata group might be in the early phases of a Wilsonian taxon cycle and that the capacity to tolerate salt stress has promoted dispersal and colonization of remote oceanic islands. Divergence itself, however, is largely driven by geographical isolation rather than shifts in ecology.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/biolinnean/blaa172","usgsCitation":"Richmond, J.Q., Ota, H., Grismer, L., and Fisher, R., 2021, Influence of niche breadth and position on the historical biogeography of seafaring scincid lizards: Biological Journal of the Linnean Society, v. 132, no. 1, p. 74-92, https://doi.org/10.1093/biolinnean/blaa172.","productDescription":"19 p.","startPage":"74","endPage":"92","ipdsId":"IP-123408","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":454152,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/biolinnean/blaa172","text":"Publisher Index Page"},{"id":391914,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Australia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 104.23828125,\n -47.04018214480665\n ],\n [\n 165.76171875,\n -47.04018214480665\n ],\n [\n 165.76171875,\n 5.61598581915534\n ],\n [\n 104.23828125,\n 5.61598581915534\n ],\n [\n 104.23828125,\n -47.04018214480665\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"132","issue":"1","noUsgsAuthors":false,"publicationDate":"2020-12-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Richmond, Jonathan Q. 0000-0001-9398-4894 jrichmond@usgs.gov","orcid":"https://orcid.org/0000-0001-9398-4894","contributorId":5400,"corporation":false,"usgs":true,"family":"Richmond","given":"Jonathan","email":"jrichmond@usgs.gov","middleInitial":"Q.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":827039,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ota, Hidetoshi","contributorId":147501,"corporation":false,"usgs":false,"family":"Ota","given":"Hidetoshi","email":"","affiliations":[],"preferred":false,"id":827040,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Grismer, L Lee","contributorId":269404,"corporation":false,"usgs":false,"family":"Grismer","given":"L Lee","affiliations":[{"id":41086,"text":"La Sierra University","active":true,"usgs":false}],"preferred":false,"id":827041,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fisher, Robert N. 0000-0002-2956-3240","orcid":"https://orcid.org/0000-0002-2956-3240","contributorId":51675,"corporation":false,"usgs":true,"family":"Fisher","given":"Robert N.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":827042,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70227144,"text":"70227144 - 2021 - Infection status as the basis for habitat choices in a wild amphibian","interactions":[],"lastModifiedDate":"2022-01-03T15:39:28.742022","indexId":"70227144","displayToPublicDate":"2020-12-04T08:52:00","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":740,"text":"American Naturalist","active":true,"publicationSubtype":{"id":10}},"title":"Infection status as the basis for habitat choices in a wild amphibian","docAbstract":"Animals challenged with disease may select specific habitat conditions that help prevent or reduce infection. Whereas preinfection avoidance of habitats with a high risk of disease exposure has been documented in both captive and free-ranging animals, evidence of switching habitats after infection to support the clearing of the infection is limited to laboratory experiments. The extent to which wild animals proximately modify habitat choices in response to infection status thus remains unclear. We investigated preinfection behavioral avoidance and postinfection habitat switching using wild, radio-tracked boreal toads (Anaxyrus boreas boreas) in a population challenged with Batrachochytrium dendrobatidis (Bd), a pathogenic fungus responsible for a catastrophic panzootic affecting hundreds of amphibian species worldwide. Boreal toads did not preemptively avoid microhabitats with conditions conducive to Bd growth. Infected individuals, however, selected warmer, more open habitats, which were associated with elevated body temperature and the subsequent clearing of infection. Our results suggest that disease can comprise an important selective pressure on animal habitat and space use. Habitat selection models, therefore, may be greatly improved by including variables that quantify infection risk and/or the infection status of individuals through time.
","language":"English","publisher":"University of Chicago Press","doi":"10.1086/711927","usgsCitation":"Barrile, G.M., Chalfoun, A.D., and Walters, A.W., 2021, Infection status as the basis for habitat choices in a wild amphibian: American Naturalist, v. 197, no. 1, p. 128-137, https://doi.org/10.1086/711927.","productDescription":"10 p.","startPage":"128","endPage":"137","ipdsId":"IP-107230","costCenters":[{"id":683,"text":"Wyoming Cooperative Fish and Wildlife Research Unit","active":false,"usgs":true}],"links":[{"id":454157,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1086/711927","text":"Publisher Index Page"},{"id":393736,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","otherGeospatial":"Bridger-Teton National Forest","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -110.5,\n 42.5\n ],\n [\n -110.35,\n 42.5\n ],\n [\n -110.35,\n 43\n ],\n [\n -110.5,\n 43\n ],\n [\n -110.5,\n 42.5\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"197","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Barrile, Gabriel M.","contributorId":270694,"corporation":false,"usgs":false,"family":"Barrile","given":"Gabriel","email":"","middleInitial":"M.","affiliations":[{"id":40829,"text":"uwy","active":true,"usgs":false}],"preferred":false,"id":829777,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chalfoun, Anna D. 0000-0002-0219-6006 achalfoun@usgs.gov","orcid":"https://orcid.org/0000-0002-0219-6006","contributorId":197589,"corporation":false,"usgs":true,"family":"Chalfoun","given":"Anna","email":"achalfoun@usgs.gov","middleInitial":"D.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":829778,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Walters, Annika W. 0000-0002-8638-6682 awalters@usgs.gov","orcid":"https://orcid.org/0000-0002-8638-6682","contributorId":4190,"corporation":false,"usgs":true,"family":"Walters","given":"Annika","email":"awalters@usgs.gov","middleInitial":"W.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":829776,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70217085,"text":"70217085 - 2021 - Factors affecting nitrate concentrations in stream base flow","interactions":[],"lastModifiedDate":"2021-07-02T13:38:46.739023","indexId":"70217085","displayToPublicDate":"2020-12-04T07:16:19","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5925,"text":"Environmental Science and Technology","active":true,"publicationSubtype":{"id":10}},"title":"Factors affecting nitrate concentrations in stream base flow","docAbstract":"Elevated nitrogen concentrations in streams and rivers in the Chesapeake Bay watershed have adversely affected the ecosystem health of the bay. Much of this nitrogen is derived as nitrate from groundwater that discharges to streams as base flow. In this study, boosted regression trees (BRTs) were used to relate nitrate concentrations in base flow (n = 156) to explanatory variables describing nitrogen sources, geology, and soil and catchment characteristics. From these relations, a BRT model was developed to predict base flow nitrate concentrations in streams throughout the Chesapeake Bay watershed. The highest base flow nitrate concentrations were associated with intensive agricultural land use, carbonate geology, and sparse riparian canopy, which suggested that reduced nitrogen inputs, particularly over carbonate terrane, are critical for limiting nitrate concentrations. The lowest nitrate concentrations in the BRT model were associated with extensive riparian canopy, high levels of organic carbon in soils, and suboxic conditions at shallow depths, which suggested that denitrification in the subsurface, particularly in the riparian zone, is limiting base flow nitrate concentrations. Nitrate transport from aquifers to streams can take decades to occur, resulting in decades-long lag times between the time when a land-use activity is implemented and when its effects are fully observed in streams. Predictive models of base flow nitrate concentrations in streams will help identify which portions of a watershed are likely to have large fractions of total stream nitrogen load derived from pathways with significant lag times.
","language":"English","publisher":"American Chemical Society","doi":"10.1021/acs.est.0c02495","usgsCitation":"Wherry, S., Tesoriero, A.J., and Terziotti, S., 2021, Factors affecting nitrate concentrations in stream base flow: Environmental Science and Technology, v. 55, no. 2, p. 902-911, https://doi.org/10.1021/acs.est.0c02495.","productDescription":"10 p.","startPage":"902","endPage":"911","ipdsId":"IP-109230","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":436629,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9RXR45G","text":"USGS data release","linkHelpText":"Input and results from a boosted regression tree (BRT) model relating base flow nitrate concentrations in the Chesapeake Bay watershed to catchment characteristics (1970-2013)"},{"id":381871,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Delaware, Maryland, New York, North Carolina, Pennsylvania, Virginia, West Virginia","otherGeospatial":"Chesapeake Bay watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.1904296875,\n 38.41916639395372\n ],\n [\n -75.223388671875,\n 38.64261790634527\n ],\n [\n -75.35522460937499,\n 38.79690830348427\n ],\n [\n -75.498046875,\n 38.87392853923629\n ],\n [\n -75.5419921875,\n 39.0533181067413\n ],\n [\n -75.662841796875,\n 39.30029918615029\n ],\n [\n -75.750732421875,\n 39.70718665682654\n ],\n [\n -75.6298828125,\n 40.052847601823984\n ],\n [\n -75.69580078125,\n 40.07807142745009\n ],\n [\n -75.95947265625,\n 40.052847601823984\n ],\n [\n -76.0693359375,\n 40.069664523297774\n ],\n [\n -76.058349609375,\n 40.18726672309203\n ],\n [\n -75.9375,\n 40.29628651711716\n ],\n [\n -75.91552734375,\n 40.3549167507906\n ],\n [\n -75.89355468749999,\n 40.47202439692057\n ],\n [\n -76.09130859375,\n 40.56389453066509\n ],\n [\n -76.190185546875,\n 40.64730356252251\n ],\n [\n -76.0693359375,\n 40.75557964275589\n ],\n [\n -75.83862304687499,\n 40.871987756697415\n ],\n [\n -75.76171875,\n 40.91351257612758\n ],\n [\n -75.706787109375,\n 40.95501133048621\n ],\n [\n -75.7177734375,\n 41.071069130806414\n ],\n [\n -75.662841796875,\n 41.1455697310095\n ],\n [\n -75.5419921875,\n 41.13729606112276\n ],\n [\n -75.322265625,\n 41.104190944576466\n ],\n [\n -75.377197265625,\n 41.22824901518529\n ],\n [\n -75.377197265625,\n 41.28606238749825\n ],\n [\n -75.377197265625,\n 41.43449030894922\n ],\n [\n -75.399169921875,\n 41.6154423246811\n ],\n [\n -75.34423828125,\n 41.68111756290652\n ],\n [\n -75.2783203125,\n 41.91045347666418\n ],\n [\n -75.38818359375,\n 42.00848901572399\n ],\n [\n -75.377197265625,\n 42.09007006868398\n ],\n [\n -75.223388671875,\n 42.17968819665961\n ],\n [\n -74.970703125,\n 42.26917949243506\n ],\n [\n -74.8388671875,\n 42.32606244456202\n ],\n [\n -74.520263671875,\n 42.415346114253616\n ],\n [\n -74.278564453125,\n 42.54498667313236\n ],\n [\n -74.322509765625,\n 42.64204079304426\n ],\n [\n -74.410400390625,\n 42.80346172417078\n ],\n [\n -74.68505859374999,\n 42.924251753870685\n ],\n [\n -75.069580078125,\n 42.98053954751642\n ],\n [\n -75.38818359375,\n 42.96446257387128\n ],\n [\n -75.684814453125,\n 42.93229601903058\n ],\n [\n -75.9375,\n 42.87596410238256\n ],\n [\n -76.201171875,\n 42.827638636242284\n ],\n [\n -76.26708984375,\n 42.72280375732727\n ],\n [\n -76.2890625,\n 42.601619944327965\n ],\n [\n -76.2890625,\n 42.52069952914966\n ],\n [\n -76.343994140625,\n 42.415346114253616\n ],\n [\n -76.46484375,\n 42.382894009614034\n ],\n [\n -76.640625,\n 42.431565872579185\n ],\n [\n -76.7724609375,\n 42.39912215986002\n ],\n [\n -76.80541992187499,\n 42.24478535602799\n ],\n [\n -76.88232421875,\n 42.285437007491545\n ],\n [\n -76.9482421875,\n 42.415346114253616\n ],\n [\n -77.04711914062499,\n 42.44778143462245\n ],\n [\n -77.14599609375,\n 42.415346114253616\n ],\n [\n -77.2998046875,\n 42.382894009614034\n ],\n [\n -77.222900390625,\n 42.54498667313236\n ],\n [\n -77.442626953125,\n 42.69858589169842\n ],\n [\n -77.574462890625,\n 42.60970621339408\n ],\n [\n -77.640380859375,\n 42.48830197960227\n ],\n [\n -77.728271484375,\n 42.439674178149424\n ],\n [\n -77.6513671875,\n 42.31793945446847\n ],\n [\n -77.596435546875,\n 42.22851735620852\n ],\n [\n -77.5634765625,\n 42.09007006868398\n ],\n [\n -77.6953125,\n 41.92680320648791\n ],\n [\n -77.9150390625,\n 41.83682786072714\n ],\n [\n -78.0908203125,\n 41.795888098191426\n ],\n [\n -78.453369140625,\n 41.599013054830216\n ],\n [\n -78.453369140625,\n 41.50857729743935\n ],\n [\n -78.42041015625,\n 41.376808565702355\n ],\n [\n -78.3984375,\n 41.21172151054787\n ],\n [\n -78.519287109375,\n 41.054501963290505\n ],\n [\n -78.541259765625,\n 40.9218144123785\n ],\n [\n -78.409423828125,\n 40.713955826286046\n ],\n [\n -78.299560546875,\n 40.55554790286311\n ],\n [\n -78.343505859375,\n 40.48873742102282\n ],\n [\n -78.475341796875,\n 40.30466538259176\n ],\n [\n -78.64013671875,\n 40.06125658140474\n ],\n [\n -78.826904296875,\n 39.9434364619742\n ],\n [\n -78.848876953125,\n 39.80853604144591\n ],\n [\n -78.85986328125,\n 39.715638134796336\n ],\n [\n -78.99169921875,\n 39.69873414348139\n ],\n [\n -79.046630859375,\n 39.64799732373418\n ],\n [\n -79.266357421875,\n 39.436192999314095\n ],\n [\n -79.420166015625,\n 39.2832938689385\n ],\n [\n -79.354248046875,\n 39.26628442213066\n ],\n [\n -79.266357421875,\n 39.232253141714885\n ],\n [\n -79.2333984375,\n 39.155622393423215\n ],\n [\n -79.244384765625,\n 39.01918369029134\n ],\n [\n -79.27734374999999,\n 38.89103282648846\n ],\n [\n -79.398193359375,\n 38.74551518488265\n ],\n [\n -79.661865234375,\n 38.54816542304656\n ],\n [\n -79.683837890625,\n 38.47079371120379\n ],\n [\n -79.727783203125,\n 38.34165619279595\n ],\n [\n -79.815673828125,\n 38.20365531807149\n ],\n [\n -80.04638671875,\n 38.013476231041935\n ],\n [\n -80.17822265625,\n 37.779398571318765\n ],\n [\n -80.2880859375,\n 37.59682400108367\n ],\n [\n -80.4638671875,\n 37.47485808497102\n ],\n [\n -80.694580078125,\n 37.38761749978395\n ],\n [\n -80.771484375,\n 37.23032838760387\n ],\n [\n -80.57373046875,\n 37.26530995561875\n ],\n [\n -80.44189453125,\n 37.309014074275915\n ],\n [\n -80.255126953125,\n 37.31775185163688\n ],\n [\n -80.013427734375,\n 37.3002752813443\n ],\n [\n -79.8486328125,\n 37.23907530202184\n ],\n [\n -79.771728515625,\n 37.18657859524883\n ],\n [\n -79.6728515625,\n 37.07271048132943\n ],\n [\n -79.541015625,\n 37.09900294387622\n ],\n [\n -79.354248046875,\n 37.142803443716836\n ],\n [\n -79.1455078125,\n 37.10776507118514\n ],\n [\n -79.112548828125,\n 37.055177106660814\n ],\n [\n -78.936767578125,\n 36.932330061503144\n ],\n [\n -78.837890625,\n 36.94111143010769\n ],\n [\n -78.662109375,\n 37.055177106660814\n ],\n [\n -78.486328125,\n 37.03763967977139\n ],\n [\n -78.42041015625,\n 36.94111143010769\n ],\n [\n -78.20068359374999,\n 36.96744946416934\n ],\n [\n -77.904052734375,\n 37.03763967977139\n ],\n [\n -77.750244140625,\n 37.081475648860525\n ],\n [\n -77.53051757812499,\n 37.081475648860525\n ],\n [\n -77.354736328125,\n 37.07271048132943\n ],\n [\n -77.069091796875,\n 37.081475648860525\n ],\n [\n -76.959228515625,\n 37.01132594307015\n ],\n [\n -76.893310546875,\n 36.932330061503144\n ],\n [\n -76.871337890625,\n 36.83566824724438\n ],\n [\n -76.849365234375,\n 36.677230602346214\n ],\n [\n -76.7724609375,\n 36.527294814546245\n ],\n [\n -76.629638671875,\n 36.55377524336089\n ],\n [\n -76.46484375,\n 36.589068371399115\n ],\n [\n -76.35498046875,\n 36.48314061639213\n ],\n [\n -76.256103515625,\n 36.57142382346277\n ],\n [\n -76.190185546875,\n 36.66841891894786\n ],\n [\n -76.0693359375,\n 36.65079252503471\n ],\n [\n -75.9375,\n 36.66841891894786\n ],\n [\n -75.948486328125,\n 36.76529191711624\n ],\n [\n -75.904541015625,\n 37.01132594307015\n ],\n [\n -75.926513671875,\n 37.17782559332976\n ],\n [\n -75.882568359375,\n 37.42252593456307\n ],\n [\n -75.618896484375,\n 37.640334898059486\n ],\n [\n -75.509033203125,\n 37.82280243352756\n ],\n [\n -75.38818359375,\n 38.013476231041935\n ],\n [\n -75.16845703124999,\n 38.272688535980976\n ],\n [\n -75.1904296875,\n 38.41916639395372\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"55","issue":"2","noUsgsAuthors":false,"publicationDate":"2020-12-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Wherry, Susan 0000-0002-6749-8697 swherry@usgs.gov","orcid":"https://orcid.org/0000-0002-6749-8697","contributorId":140159,"corporation":false,"usgs":true,"family":"Wherry","given":"Susan","email":"swherry@usgs.gov","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":807557,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tesoriero, Anthony J. 0000-0003-4674-7364 tesorier@usgs.gov","orcid":"https://orcid.org/0000-0003-4674-7364","contributorId":2693,"corporation":false,"usgs":true,"family":"Tesoriero","given":"Anthony","email":"tesorier@usgs.gov","middleInitial":"J.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":807558,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Terziotti, Silvia 0000-0003-3559-5844 seterzio@usgs.gov","orcid":"https://orcid.org/0000-0003-3559-5844","contributorId":1613,"corporation":false,"usgs":true,"family":"Terziotti","given":"Silvia","email":"seterzio@usgs.gov","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":476,"text":"North Carolina Water Science Center","active":true,"usgs":true}],"preferred":true,"id":807559,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70217206,"text":"70217206 - 2021 - The birth of a Hawaiian fissure eruption","interactions":[],"lastModifiedDate":"2021-01-12T12:59:59.391343","indexId":"70217206","displayToPublicDate":"2020-12-04T06:52:43","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7167,"text":"Journal of Geophysical Research: Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"The birth of a Hawaiian fissure eruption","docAbstract":"Most basaltic explosive eruptions intensify abruptly, allowing little time to document processes at the start of eruption. One opportunity came with the initiation of activity from fissure 8 (F8) during the 2018 eruption on the lower East Rift Zone of Kīlauea, Hawaii. F8 erupted in four episodes. We recorded 28 min of high‐definition video during a 51‐min period, capturing the onset of the second episode on 5 May. From the videos, we were able to analyze the following in‐flight parameters: frequency and duration of explosions; ejecta heights; pyroclast exit velocities; in‐flight total mass and estimated mass eruption rates; and the in‐flight total grain size distributions. The videos record a transition from initial pulsating outgassing, via spaced, but increasingly rapid, discrete explosions, to quasisustained, unsteady fountaining. This transition accompanied waxing intensity (mass flux) of the F8 eruption. We infer that all activity was driven by a combination of the ascent of a coupled mixture of small bubbles and melt, and the buoyant rise of decoupled gas slugs and/or pockets. The balance between these two types of concurrent flow determined the exact form of the eruptive activity at any point in time, and changes to their relative contributions drove the transition we observed at early F8. Qualitative observations of other Hawaiian fountains at Kīlauea suggest that this physical model may apply more generally. This study demonstrates the value of in‐flight parameters derived from high‐resolution videos, which offer a rapid and highly time‐sensitive alternative to measurements based on sampling of deposits posteruption.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2020JB020903","usgsCitation":"Houghton, B.F., Tisdale, C.M., Llewellin, E.W., Taddeucci, J., Orr, T.R., Walker, B.H., and Patrick, M.R., 2021, The birth of a Hawaiian fissure eruption: Journal of Geophysical Research: Solid Earth, v. 126, no. 1, e2020JB020903, 17 p., https://doi.org/10.1029/2020JB020903.","productDescription":"e2020JB020903, 17 p.","ipdsId":"IP-120595","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":454165,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://durham-repository.worktribe.com/output/1255250","text":"External Repository"},{"id":382080,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Hawaii","otherGeospatial":"Island of Hawai'i","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -156.11572265624997,\n 18.875102750356465\n ],\n [\n -154.79736328124997,\n 18.875102750356465\n ],\n [\n -154.79736328124997,\n 20.324023603422518\n ],\n [\n -156.11572265624997,\n 20.324023603422518\n ],\n [\n -156.11572265624997,\n 18.875102750356465\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"126","issue":"1","noUsgsAuthors":false,"publicationDate":"2021-01-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Houghton, Bruce F. 0000-0002-7532-9770","orcid":"https://orcid.org/0000-0002-7532-9770","contributorId":140077,"corporation":false,"usgs":false,"family":"Houghton","given":"Bruce","email":"","middleInitial":"F.","affiliations":[{"id":6977,"text":"University of Hawai`i at Hilo","active":true,"usgs":false},{"id":13351,"text":"University of Hawaii Cooperative Studies Unit","active":true,"usgs":false}],"preferred":false,"id":807999,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tisdale, Caroline M.","contributorId":247598,"corporation":false,"usgs":false,"family":"Tisdale","given":"Caroline","middleInitial":"M.","affiliations":[{"id":39036,"text":"University of Hawaii at Manoa","active":true,"usgs":false}],"preferred":false,"id":808000,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Llewellin, Edward W. 0000-0003-2165-7426","orcid":"https://orcid.org/0000-0003-2165-7426","contributorId":247599,"corporation":false,"usgs":false,"family":"Llewellin","given":"Edward","email":"","middleInitial":"W.","affiliations":[{"id":25252,"text":"Durham University","active":true,"usgs":false}],"preferred":true,"id":808001,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Taddeucci, Jacopo 0000-0002-0516-3699","orcid":"https://orcid.org/0000-0002-0516-3699","contributorId":184101,"corporation":false,"usgs":false,"family":"Taddeucci","given":"Jacopo","email":"","affiliations":[],"preferred":false,"id":808002,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Orr, Tim R. 0000-0003-1157-7588 torr@usgs.gov","orcid":"https://orcid.org/0000-0003-1157-7588","contributorId":149803,"corporation":false,"usgs":true,"family":"Orr","given":"Tim","email":"torr@usgs.gov","middleInitial":"R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":808003,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Walker, Brett H.","contributorId":225523,"corporation":false,"usgs":false,"family":"Walker","given":"Brett","email":"","middleInitial":"H.","affiliations":[{"id":36402,"text":"University of Hawaii","active":true,"usgs":false}],"preferred":false,"id":808004,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Patrick, Matthew R. 0000-0002-8042-6639 mpatrick@usgs.gov","orcid":"https://orcid.org/0000-0002-8042-6639","contributorId":2070,"corporation":false,"usgs":true,"family":"Patrick","given":"Matthew","email":"mpatrick@usgs.gov","middleInitial":"R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":808005,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70237317,"text":"70237317 - 2021 - Dating by cosmogenic nuclides","interactions":[],"lastModifiedDate":"2022-10-07T13:16:49.440633","indexId":"70237317","displayToPublicDate":"2020-12-02T08:13:08","publicationYear":"2021","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Dating by cosmogenic nuclides","docAbstract":"Since the 1990s, cosmogenic nuclides have revolutionized the study of Earth surface processes, particularly the understanding of rates and dates. These nuclides, including 3He, 10Be, 14C, 21Ne, 26Al, and 36Cl, enable dating of landforms and the measurement of erosion rates both at the scale of drainage basins and at specific locations on Earth's surface. Cosmogenic nuclides are produced at low rates (several to hundreds of atoms per gram per year) by the interaction of cosmic rays with elements both in the atmosphere and in surficial materials, including in rock and soil. Measuring nuclide concentrations requires elemental separation from source geologic material followed by counting of atoms using sensitive accelerator mass spectrometers. Because nuclide production rates have been quantified, the measured concentration of these nuclides can be interpreted as a near-surface residence time. Here, we review the systematics of commonly used cosmogenic nuclides, describe how they are extracted and measured, and then present case studies focusing on the most commonly measured cosmogenic nuclide, 10Be. We present common applications such as dating surface features, including moraines and outcrops shaped by glaciation, the use of cosmogenic nuclides for inferring tectonic and erosion processes in drainage basins, and the use of these nuclides to trace sediment sources in drainage basins. When multiple nuclides are measured in one sample, they can be used to model burial and exposure histories in stratigraphic sections. We conclude by exploring what the future might bring in terms of measurements and applications.
","largerWorkTitle":"Encyclopedia of geology","language":"English","publisher":"Elsevier","doi":"10.1016/B978-0-08-102908-4.00124-7","usgsCitation":"Bierman, P., Bender, A., Christ, A.J., Corbett, L.B., Halsted, C.T., Portenga, E.W., and Schmidt, A.H., 2021, Dating by cosmogenic nuclides, chap. of Encyclopedia of geology, p. 101-115, https://doi.org/10.1016/B978-0-08-102908-4.00124-7.","productDescription":"15 p.","startPage":"101","endPage":"115","ipdsId":"IP-119305","costCenters":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"links":[{"id":408085,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"edition":"Second Edition","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Bierman, Paul R.","contributorId":198743,"corporation":false,"usgs":false,"family":"Bierman","given":"Paul R.","affiliations":[{"id":17809,"text":"University of Vermont, Burlington","active":true,"usgs":false}],"preferred":false,"id":854117,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bender, Adrian 0000-0001-7469-1957","orcid":"https://orcid.org/0000-0001-7469-1957","contributorId":219952,"corporation":false,"usgs":true,"family":"Bender","given":"Adrian","affiliations":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":854118,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Christ, Andrew J.","contributorId":297429,"corporation":false,"usgs":false,"family":"Christ","given":"Andrew","email":"","middleInitial":"J.","affiliations":[{"id":13253,"text":"University of Vermont","active":true,"usgs":false}],"preferred":false,"id":854119,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Corbett, Lee B.","contributorId":152123,"corporation":false,"usgs":false,"family":"Corbett","given":"Lee","email":"","middleInitial":"B.","affiliations":[{"id":17809,"text":"University of Vermont, Burlington","active":true,"usgs":false}],"preferred":false,"id":854120,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Halsted, Christopher T.","contributorId":297431,"corporation":false,"usgs":false,"family":"Halsted","given":"Christopher","email":"","middleInitial":"T.","affiliations":[{"id":13253,"text":"University of Vermont","active":true,"usgs":false}],"preferred":false,"id":854121,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Portenga, Eric W.","contributorId":297434,"corporation":false,"usgs":false,"family":"Portenga","given":"Eric","email":"","middleInitial":"W.","affiliations":[{"id":55463,"text":"Eastern Michigan University","active":true,"usgs":false}],"preferred":false,"id":854122,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Schmidt, Amanda H.","contributorId":297436,"corporation":false,"usgs":false,"family":"Schmidt","given":"Amanda","email":"","middleInitial":"H.","affiliations":[{"id":6707,"text":"Oberlin College","active":true,"usgs":false}],"preferred":false,"id":854123,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70220115,"text":"70220115 - 2021 - Monitoring volcanic deformation","interactions":[],"lastModifiedDate":"2021-04-20T12:46:38.791152","indexId":"70220115","displayToPublicDate":"2020-12-02T07:42:30","publicationYear":"2021","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Monitoring volcanic deformation","docAbstract":"Deformation signals recorded at volcanoes have long been used to infer the processes behind subsurface magma intrusions. Monitoring strategies vary greatly depending on several factors such as the activity of the individual volcano, access, available personnel, and funding.
Certain geodetic monitoring methods, such as Electronic Distance Measurements, are inexpensive but require that scientists be dangerously close to active areas. Other techniques, such as telemetered geodetic measurements (Electronic Tiltmeters and Global Navigation Satellite System), or deformation images from Interferometric Synthetic Aperture Radar, can be collected remotely and with less risk. Observed surface deformation can be fit to the predictions of mathematical source models to obtain quantitative estimates of their parameters (e.g., location, depth, volume change and more). Combined deformation and gravity change measurements can be used to infer the density of subsurface intrusions and better constrain the source of unrest.
To be effective, geodetic monitoring must be done before, during, and after eruptions and must be integrated with other monitoring techniques (e.g., seismology, geochemistry, physical volcanology, remote sensing). It requires the long-term commitment of time and resources.
Done effectively, geodetic monitoring not only can provide timely warnings of escalating volcano hazards but may also lead to improved understanding of how volcanoes work. Even when a volcano is not active, monitoring generates baseline information against which changes in volcano behavior can be compared. Preserving the integrity and accessibility of geodetic data archives is thus essential if future volcanologists are to benefit from the decades-long records of geodetic data gathered by volcano observatories.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Encyclopedia of geology","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Academic Press","doi":"10.1016/B978-0-08-102908-4.00132-6","usgsCitation":"Battaglia, M., Alpala, J., Alpala, R., Angarita, M., Arcos, D., Euillades, L., Euillades, P., Muller, C., and Narvaez, L., 2021, Monitoring volcanic deformation, chap. of Encyclopedia of geology, p. 774-804, https://doi.org/10.1016/B978-0-08-102908-4.00132-6.","productDescription":"31 p.","startPage":"774","endPage":"804","ipdsId":"IP-119768","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":385218,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"edition":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Battaglia, Maurizio 0000-0003-4726-5287 mbattaglia@usgs.gov","orcid":"https://orcid.org/0000-0003-4726-5287","contributorId":204742,"corporation":false,"usgs":true,"family":"Battaglia","given":"Maurizio","email":"mbattaglia@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":814512,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Alpala, Jorge","contributorId":139634,"corporation":false,"usgs":false,"family":"Alpala","given":"Jorge","email":"","affiliations":[{"id":12810,"text":"Colombian Geological Survey","active":true,"usgs":false}],"preferred":false,"id":814513,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Alpala, Rosa","contributorId":215654,"corporation":false,"usgs":false,"family":"Alpala","given":"Rosa","email":"","affiliations":[{"id":12810,"text":"Colombian Geological Survey","active":true,"usgs":false}],"preferred":false,"id":814514,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Angarita, Mario","contributorId":215655,"corporation":false,"usgs":false,"family":"Angarita","given":"Mario","email":"","affiliations":[{"id":37066,"text":"OVSICORI","active":true,"usgs":false}],"preferred":false,"id":814515,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Arcos, Dario","contributorId":139636,"corporation":false,"usgs":false,"family":"Arcos","given":"Dario","affiliations":[{"id":12810,"text":"Colombian Geological Survey","active":true,"usgs":false}],"preferred":false,"id":814518,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Euillades, Leonardo","contributorId":225157,"corporation":false,"usgs":false,"family":"Euillades","given":"Leonardo","email":"","affiliations":[{"id":41053,"text":"Universidad Nacional de Cuyo, Facultad de Ingeniería, Instituto CEDIAC & CONICET","active":true,"usgs":false}],"preferred":false,"id":814516,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Euillades, Pablo","contributorId":225156,"corporation":false,"usgs":false,"family":"Euillades","given":"Pablo","affiliations":[{"id":41053,"text":"Universidad Nacional de Cuyo, Facultad de Ingeniería, Instituto CEDIAC & CONICET","active":true,"usgs":false}],"preferred":false,"id":814517,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Muller, Cyril","contributorId":205255,"corporation":false,"usgs":false,"family":"Muller","given":"Cyril","email":"","affiliations":[{"id":37066,"text":"OVSICORI","active":true,"usgs":false}],"preferred":false,"id":814519,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Narvaez, Lourdes","contributorId":215659,"corporation":false,"usgs":false,"family":"Narvaez","given":"Lourdes","email":"","affiliations":[{"id":12810,"text":"Colombian Geological Survey","active":true,"usgs":false}],"preferred":false,"id":814520,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70219582,"text":"70219582 - 2021 - Interactive PHREEQ-N-AMDTreat water-quality modeling tools to evaluate performance and design of treatment systems for acid mine drainage","interactions":[],"lastModifiedDate":"2021-04-15T12:53:09.492694","indexId":"70219582","displayToPublicDate":"2020-12-01T07:52:18","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":835,"text":"Applied Geochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Interactive PHREEQ-N-AMDTreat water-quality modeling tools to evaluate performance and design of treatment systems for acid mine drainage","docAbstract":"The PHREEQ-N-AMDTreat aqueous geochemical modeling tools described herein simulate changes in pH and solute concentrations resulting from passive and active treatment of acidic or alkaline mine drainage (AMD). The “user-friendly” interactive tools, which are publicly available software, utilize PHREEQC equilibrium aqueous and surface speciation models and kinetics models for O2 ingassing and CO2 outgassing, iron and manganese oxidation and precipitation, limestone dissolution, and organic carbon oxidation combined with reduction of nitrate, sulfate, and ferric iron. Reactions with synthetic caustic chemicals (CaO, Ca(OH)2, NaOH, Na2CO3) or oxidizing agents (H2O2) also may be simulated separately or combined with sequential kinetic steps. A user interface facilitates input of water chemistry data for one or two (mixed) influent AMD solutions and adjustment of kinetic variables. Graphical and tabular output indicates the changes in pH, metals and other solute concentrations, total dissolved solids, and specific conductance of treated effluent plus the cumulative quantity of precipitated solids as a function of retention time or the amount of caustic agent added. By adjusting kinetic variables or chemical dosing, the effects of independent or sequential treatment steps that have different retention time (volume/flow rate), aeration rate, quantities of reactive solids, and temperature can be simulated for the specified influent quality. The size (land area) of a treatment system can then be estimated using reaction time estimates (volume for a corresponding treatment step is the product of reaction time and flow rate; area is volume divided by depth). Given the estimated system size, the AMDTreat cost-analysis model may be used to compute approximate costs for installation (capital) and annual operations and maintenance. Thus, various passive and/or active treatment strategies can be identified that could potentially achieve the desired effluent quality, but require different land area, equipment, and costs for construction and operation.
Quantifiable estimates of predator–prey interactions and relationships in aquatic habitats are difficult to obtain and rare, especially when individuals cannot be readily observed. To overcome this observational impediment, imaging sonar was used to assess the cooccurrence of predator‐size fish and juvenile salmonids, Oncorhynchus spp., at the entrance to a floating surface collector (FSC) in the forebay of North Fork Dam on the Clackamas River, Oregon (USA). Imaging sonar can be used to transform active sound waves into visual data, making it possible to obtain continuous underwater observations on the presence and interspecific interactions between predator‐size fish and prey (juvenile salmonids). Hourly counts of smolt‐size fish tracks, diel phase, water clarity and river discharge were used as covariates within a zero‐inflated Poisson model to determine how these factors may influence the number of predators in front of the FSC. Both the number of smolt‐size fish tracks and diel phase had the strongest effects on the number of predator‐size fish tracks, with more predator‐size fish tracks observed during the daytime, and as the number of smolt‐size fish tracks increased. Additionally, the presence of predator‐size fish may affect the abundance and direction of travel of juvenile salmonids, as fewer smolt‐size fish were observed when predators were present, and a greater proportion of smolt‐size fish were observed travelling away from the FSC when predator‐size fish were present. This study provides estimates of predator and prey fish abundance in the vicinity of surface collection systems at moderate‐sized hydropower projects and could help resource managers better understand mechanisms that can influence the survival and passage behaviour of juvenile salmonids using surface collection structures at dams.
","language":"English","publisher":"Wiley","doi":"10.1111/fme.12465","usgsCitation":"Smith, C.D., Plumb, J., Adams, N.S., and Wyatt, G.J., 2021, Predator and prey events at the entrance of a surface‐oriented fish collector at North Fork Dam, Oregon: Fisheries Management and Ecology, v. 28, no. 2, p. 172-182, https://doi.org/10.1111/fme.12465.","productDescription":"11 p.","startPage":"172","endPage":"182","ipdsId":"IP-097283","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":384347,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","city":"Estacada","otherGeospatial":"North Fork Dam","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.38632202148438,\n 45.273920035433605\n ],\n [\n -122.27645874023438,\n 45.273920035433605\n ],\n [\n -122.27645874023438,\n 45.319323121350145\n ],\n [\n -122.38632202148438,\n 45.319323121350145\n ],\n [\n -122.38632202148438,\n 45.273920035433605\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"28","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Smith, Collin D. 0000-0003-4184-5686 cdsmith@usgs.gov","orcid":"https://orcid.org/0000-0003-4184-5686","contributorId":3111,"corporation":false,"usgs":true,"family":"Smith","given":"Collin","email":"cdsmith@usgs.gov","middleInitial":"D.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":811722,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Plumb, John M. 0000-0003-4255-1612","orcid":"https://orcid.org/0000-0003-4255-1612","contributorId":220178,"corporation":false,"usgs":true,"family":"Plumb","given":"John","middleInitial":"M.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":811723,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Adams, Noah S. 0000-0002-8354-0293 nadams@usgs.gov","orcid":"https://orcid.org/0000-0002-8354-0293","contributorId":3521,"corporation":false,"usgs":true,"family":"Adams","given":"Noah","email":"nadams@usgs.gov","middleInitial":"S.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":811724,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wyatt, Garth J","contributorId":214904,"corporation":false,"usgs":false,"family":"Wyatt","given":"Garth","email":"","middleInitial":"J","affiliations":[{"id":39135,"text":"Portland General Electric, 33831 Faraday Rd., Estacada, Oregon 97023","active":true,"usgs":false}],"preferred":false,"id":811725,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70216762,"text":"70216762 - 2021 - Characterizing patterns of genomic variation in the threatened Utah prairie dog: Implications for conservation and management","interactions":[],"lastModifiedDate":"2021-05-14T11:49:09.559193","indexId":"70216762","displayToPublicDate":"2020-11-29T08:40:12","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1601,"text":"Evolutionary Applications","active":true,"publicationSubtype":{"id":10}},"title":"Characterizing patterns of genomic variation in the threatened Utah prairie dog: Implications for conservation and management","docAbstract":"Utah prairie dogs (Cynomys parvidens) are federally threatened due to eradication campaigns, habitat destruction, and outbreaks of plague. Today, Utah prairie dogs exist in small, isolated populations, making them less demographically stable and more susceptible to erosion of genetic variation by genetic drift. We characterized patterns of genetic structure at neutral and putatively adaptive loci in order to evaluate the relative effects of genetic drift and local adaptation on population divergence. We sampled individuals across the Utah prairie dog species range and generated 2,955 single nucleotide polymorphisms (SNPs) using double digest restriction site associated DNA sequencing (ddRAD). Genetic diversity was lower in low elevation sites compared to high elevation sites. Population divergence was high among sites and followed an isolation‐by‐distance (IBD) model. Our results indicate that genetic drift plays a substantial role in the population divergence of the Utah prairie dog, and colonies would likely benefit from translocation of individuals between recovery units, which are characterized by distinct elevations, despite the detection of environmental associations with outlier loci. By understanding the processes that shape genetic structure, better informed decisions can be made with respect to the management of threatened species to ensure that adaptation is not stymied.
Climate change is causing rapid warming and altered precipitation patterns in mountain watersheds, both of which influence the timing of ice breakup in mountain lakes. To enable predictions of ice breakup in the future, we analyzed a dataset of mountain lake ice breakup dates derived from remote sensing and historical downscaled climate data. We evaluated drivers of ice breakup, constructed a predictive statistical model, and developed projections of mountain lake ice breakup date with global climate models. Using Random Forest analysis, we determined that winter and spring cumulative snow fraction (portion of precipitation falling as snow) and air temperature are the strongest predictors of ice breakup on mountain lakes. Interactions between precipitation, cumulative winter air temperature and lake surface area indicate that shifts in air temperature and precipitation affect smaller lakes (< 2 km2) more than larger lakes (> 2–10 km2). A linear mixed effects model (RMSE of 18 d), applied with an ensemble of 15 global climate models, projected that end-of-century ice breakup in mountain lakes will be earlier by 25 ± 4 and 61 ± 5 (mean ± SE) days for representative concentration pathways 4.5 and 8.5, respectively.
","language":"English","publisher":"Association for the Sciences of Limnology and Oceanography","doi":"10.1002/lno.11656","usgsCitation":"Caldwell, T.J., Chandra, S., Albright, T., Harpold, A., Dills, T., Greenberg, J., Sadro, S., and Dettinger, M.D., 2021, Drivers and projections of ice phenology in mountain lakes in the western United States: Limnology and Oceanography, v. 66, no. 3, p. 995-1008, https://doi.org/10.1002/lno.11656.","productDescription":"14 p.","startPage":"995","endPage":"1008","ipdsId":"IP-104573","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":454196,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/lno.11656","text":"Publisher Index Page"},{"id":387042,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Idaho, Oregon, Washington","otherGeospatial":"Cascade Mountains, northern Rocky Mountains, Sierra Nevada Mountains","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.136474609375,\n 48.07807894349862\n ],\n [\n -116.378173828125,\n 49.001843917978526\n ],\n [\n -119.36645507812499,\n 49.001843917978526\n ],\n [\n -119.20166015625,\n 48.52388120259336\n ],\n [\n -117.191162109375,\n 47.66538735632654\n ],\n [\n -116.42211914062499,\n 47.65058757118734\n ],\n [\n -116.114501953125,\n 47.71715357016648\n ],\n [\n -116.136474609375,\n 48.07807894349862\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.76171875,\n 46.475699386607516\n ],\n [\n -119.84985351562499,\n 48.96579381461063\n ],\n [\n -121.78344726562499,\n 49.01625665778159\n ],\n [\n -122.1240234375,\n 47.04766864046083\n ],\n [\n -122.58544921875,\n 45.506346901083425\n ],\n [\n -123.1787109375,\n 42.73087427928485\n ],\n [\n -122.54150390625,\n 42.04113400940807\n ],\n [\n -122.27783203125,\n 41.1290213474951\n ],\n [\n -120.87158203125,\n 41.393294288784865\n ],\n [\n -120.9814453125,\n 42.08191667830631\n ],\n [\n -121.62963867187499,\n 43.98491011404692\n ],\n [\n -121.14624023437499,\n 45.18978009667531\n ],\n [\n -120.76171875,\n 46.475699386607516\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.45507812500001,\n 36.19109202182454\n ],\n [\n -119.794921875,\n 39.01064750994083\n ],\n [\n -120.498046875,\n 40.49709237269567\n ],\n [\n -120.52001953124999,\n 40.94671366508002\n ],\n [\n -121.6845703125,\n 40.56389453066509\n ],\n [\n -120.73974609374999,\n 38.47939467327645\n ],\n [\n -118.23486328125,\n 35.47856499535729\n ],\n [\n -116.87255859374999,\n 35.65729624809628\n ],\n [\n -116.45507812500001,\n 36.19109202182454\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"66","issue":"3","noUsgsAuthors":false,"publicationDate":"2020-11-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Caldwell, Timothy J","contributorId":146463,"corporation":false,"usgs":false,"family":"Caldwell","given":"Timothy","email":"","middleInitial":"J","affiliations":[{"id":16704,"text":"University of Nevada - Reno","active":true,"usgs":false}],"preferred":false,"id":818862,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chandra, Sudeep 0000-0002-9297-8211","orcid":"https://orcid.org/0000-0002-9297-8211","contributorId":224786,"corporation":false,"usgs":false,"family":"Chandra","given":"Sudeep","email":"","affiliations":[{"id":32871,"text":"University of Nevada at Reno","active":true,"usgs":false}],"preferred":false,"id":818863,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Albright, Thomas","contributorId":260809,"corporation":false,"usgs":false,"family":"Albright","given":"Thomas","affiliations":[{"id":12742,"text":"University of Nevada Reno","active":true,"usgs":false}],"preferred":false,"id":818864,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Harpold, Adrian","contributorId":207118,"corporation":false,"usgs":false,"family":"Harpold","given":"Adrian","affiliations":[{"id":37455,"text":"University of Nevada","active":true,"usgs":false}],"preferred":false,"id":818865,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dills, Thomas","contributorId":260810,"corporation":false,"usgs":false,"family":"Dills","given":"Thomas","email":"","affiliations":[{"id":12742,"text":"University of Nevada Reno","active":true,"usgs":false}],"preferred":false,"id":818866,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Greenberg, Jonathan","contributorId":260811,"corporation":false,"usgs":false,"family":"Greenberg","given":"Jonathan","affiliations":[{"id":12742,"text":"University of Nevada Reno","active":true,"usgs":false}],"preferred":false,"id":818867,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Sadro, Steven 0000-0002-6416-3840","orcid":"https://orcid.org/0000-0002-6416-3840","contributorId":139662,"corporation":false,"usgs":false,"family":"Sadro","given":"Steven","email":"","affiliations":[{"id":12871,"text":"Marine Science Institute, University of California, Santa Barbara, CA, USA","active":true,"usgs":false}],"preferred":false,"id":818868,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Dettinger, Michael D. 0000-0002-7509-7332 mddettin@usgs.gov","orcid":"https://orcid.org/0000-0002-7509-7332","contributorId":149896,"corporation":false,"usgs":true,"family":"Dettinger","given":"Michael","email":"mddettin@usgs.gov","middleInitial":"D.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":818869,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70226156,"text":"70226156 - 2021 - Basalt geochemistry and mantle flow during early backarc basin evolution: Havre Trough and Kermadec Arc, southwest Pacific","interactions":[],"lastModifiedDate":"2021-11-15T12:16:43.251541","indexId":"70226156","displayToPublicDate":"2020-11-27T06:14:35","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9540,"text":"Geochemistry Geophysics Geosystems","active":true,"publicationSubtype":{"id":10}},"title":"Basalt geochemistry and mantle flow during early backarc basin evolution: Havre Trough and Kermadec Arc, southwest Pacific","docAbstract":"The Havre Trough (HT) backarc basin in the southwest Pacific is in the rifting stage of development. We distinguish five types of basalt there based on their amount and kind of slab component: backarc basalts (BAB) with little or no slab component, modified BAB with slight amounts, reararc (RA) with more, remnants of the preexisting arc (Colville Ridge horsts), and arc front volcanoes within the HT. Previous subarc mantle is quickly removed and replaced by more fertile mantle with less slab component. The ambient mantle is “Pacific” isotopically, and more enriched in Nb/Yb and Nd and Hf isotope ratios north of the Central Kermadec Discontinuity at 32°S than to the south. The contrast may reflect inheritance in the south of mantle that was depleted during spreading that formed the southern South Fiji Basin and a higher degree of melting because of a wetter slab-derived flux. The slab component also differs along strike, more like a dry melt in the north and a supercritical fluid in the south. The mass fraction of slab component increases southward in the backarc as well as the arc front. RA volcanoes have the most slab component (1%–2%) and form indistinct ridges at high angles to, and <50 km behind, frontal volcanoes. Backarc basalts have less and occur throughout the basin. Slab components are distributed further into the backarc, and more irregularly, during the rifting than spreading stage of backarc basin development. The rifting stage is disorganized geochemically as well as spatially.
Spatial capture‐recapture (SCR) has emerged as the industry standard for estimating population density by leveraging information from spatial locations of repeat encounters of individuals. The precision of density estimates depends fundamentally on the number and spatial configuration of traps. Despite this knowledge, existing sampling design recommendations are heuristic and their performance remains untested for most practical applications. To address this issue, we propose a genetic algorithm that minimizes any sensible, criteria‐based objective function to produce near‐optimal sampling designs. To motivate the idea of optimality, we compare the performance of designs optimized using three model‐based criteria related to the probability of capture. We use simulation to show that these designs out‐perform those based on existing recommendations in terms of bias, precision, and accuracy in the estimation of population size. Our approach, available as a function in the R package oSCR, allows conservation practitioners and researchers to generate customized and improved sampling designs for wildlife monitoring.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecy.3262","usgsCitation":"Dupont, G., Royle, J.A., Nawaz, M., and Sutherland, C., 2021, Optimal sampling design for spatial capture‐recapture: Ecology, v. 102, no. 3, e03262, https://doi.org/10.1002/ecy.3262.","productDescription":"e03262","ipdsId":"IP-118217","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":454202,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1002/ecy.3262","text":"External Repository"},{"id":380979,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"102","issue":"3","noUsgsAuthors":false,"publicationDate":"2021-02-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Dupont, Gates","contributorId":245387,"corporation":false,"usgs":false,"family":"Dupont","given":"Gates","email":"","affiliations":[{"id":49179,"text":"University of Massachusetts-Amherst","active":true,"usgs":false}],"preferred":false,"id":806101,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Royle, J. Andrew 0000-0003-3135-2167 aroyle@usgs.gov","orcid":"https://orcid.org/0000-0003-3135-2167","contributorId":139626,"corporation":false,"usgs":true,"family":"Royle","given":"J.","email":"aroyle@usgs.gov","middleInitial":"Andrew","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":806102,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nawaz, Muhammad Ali","contributorId":245388,"corporation":false,"usgs":false,"family":"Nawaz","given":"Muhammad Ali","affiliations":[{"id":49180,"text":"Snow Leopard Trust","active":true,"usgs":false}],"preferred":false,"id":806103,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sutherland, Chris","contributorId":245389,"corporation":false,"usgs":false,"family":"Sutherland","given":"Chris","affiliations":[{"id":49181,"text":"Univ. Massachusetts-Amherst","active":true,"usgs":false}],"preferred":false,"id":806104,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70217292,"text":"70217292 - 2021 - Time-to-detection occupancy methods: Performance and utility for improving efficiency of surveys","interactions":[],"lastModifiedDate":"2021-04-08T14:31:35.82274","indexId":"70217292","displayToPublicDate":"2020-11-25T07:56:53","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"Time-to-detection occupancy methods: Performance and utility for improving efficiency of surveys","docAbstract":"Occupancy methods propelled the quantitative study of species distributions forward by separating the observation process, or the imperfect detectability of species, from the ecological processes of interest governing species distributions. Occupancy studies come at a cost, however: the collection of additional data to account for nondetections at sites where the species is present. The most common occupancy designs (repeated measures designs) require repeat visits to sites or the use of multiple observers or detection methods. Time‐to‐detection methods have been identified as a potentially efficient alternative, requiring only one visit to each site by a single observer. A comparison of time‐to‐detection methods to repeated measures designs for visual encounter surveys would allow researchers to evaluate whether time‐to‐detection methods might be appropriate for their study system and can inform optimal survey design. We collected time‐to‐detection data during two different repeated measures design occupancy surveys for four amphibians and compared the performance of time‐to‐detection methods to the other designs using the location (potential bias) and precision of posterior distributions for occurrence parameters. We further used results of time‐to‐detection surveys to optimize survey design. Time‐to‐detection methods performed best for species that are widespread and have high detection probabilities and rates, but performed less well for cryptic species with lower probability of occurrence or whose detection was strongly affected by survey conditions. In all cases single surveys were most efficient in terms of person‐hours expended, but under some conditions the survey duration required to achieve high detection probabilities would be prohibitively long for a single survey. Regardless of occupancy survey design, time‐to‐detection methods provide important information that can be used to optimize surveys, allowing researchers and resource managers to efficiently achieve monitoring and conservation goals. Collecting time‐to‐detection data while conducting repeated measures occupancy surveys requires only small modifications to field methods but could have large benefits in terms of time spent surveying in the long‐term.
Climate warming is expected to have substantial impacts on native trout across the Rocky Mountains, but there is little understanding of how these changes affect future distributions of co-occurring native fishes within population strongholds. We used mixed-effects logistic regression to investigate the role of abiotic (e.g., temperature) and biotic factors (bull trout presence, Salvelinus confluentus) on distributions of westslope cutthroat trout (Oncorhynchus clarkii lewisi; WCT) in the North Fork Flathead River, USA and Canada. The probability of WCT presence increased with stream temperature and decreased with channel gradient and bull trout presence, yet the effect of bull trout was reduced with increasing pool densities. Combining this model with spatially explicit stream temperature projections, we predict a 29% increase in suitable habitat under high emissions through 2075, with gains at mid-elevation sites predicted to exceed bull trout thermal tolerances and high-elevation sites expected to become more thermally suitable for WCT. Our study illustrates the importance of considering abiotic and biotic drivers to assess species response to climate change, helping to guide local-scale climate adaptation and management.
","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjfas-2020-0099","usgsCitation":"Heinle, K., Eby, L., Muhlfeld, C.C., Steed, A., Jones, L., D’Angelo, V.S., Whiteley, A.R., and Hubblewhite, M., 2021, Influence of water temperature and biotic interactions on the distribution of westslope cutthroat trout (Oncorhynchus clarkii lewisi) in a population stronghold under climate change: Canadian Journal of Fisheries and Aquatic Sciences, v. 78, no. 4, p. 444-456, https://doi.org/10.1139/cjfas-2020-0099.","productDescription":"13 p.","startPage":"444","endPage":"456","ipdsId":"IP-111700","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":387127,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"Alberta, British Columbia, Montana","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -113.9996337890625,\n 47.98256841921405\n ],\n [\n -113.49426269531249,\n 47.97889140226657\n ],\n [\n -113.6700439453125,\n 48.34894812401375\n ],\n [\n -113.895263671875,\n 48.669198799260045\n ],\n [\n -114.730224609375,\n 49.57510247172322\n ],\n [\n -114.993896484375,\n 49.61070993807422\n ],\n [\n -115.103759765625,\n 49.396675075193976\n ],\n [\n -114.4940185546875,\n 48.585692256886624\n ],\n [\n -113.9996337890625,\n 47.98256841921405\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"78","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Heinle, Kadie","contributorId":260877,"corporation":false,"usgs":false,"family":"Heinle","given":"Kadie","email":"","affiliations":[{"id":36523,"text":"University of Montana","active":true,"usgs":false}],"preferred":false,"id":819032,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Eby, Lisa A","contributorId":251751,"corporation":false,"usgs":false,"family":"Eby","given":"Lisa A","affiliations":[{"id":36523,"text":"University of Montana","active":true,"usgs":false}],"preferred":false,"id":819033,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Muhlfeld, Clint C. 0000-0002-4599-4059 cmuhlfeld@usgs.gov","orcid":"https://orcid.org/0000-0002-4599-4059","contributorId":924,"corporation":false,"usgs":true,"family":"Muhlfeld","given":"Clint","email":"cmuhlfeld@usgs.gov","middleInitial":"C.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":819034,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Steed, Amber","contributorId":124596,"corporation":false,"usgs":false,"family":"Steed","given":"Amber","affiliations":[{"id":5133,"text":"Montana Fish Wildlife and Parks, Kalispell, Montana 59901","active":true,"usgs":false}],"preferred":false,"id":819035,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jones, Leslie","contributorId":260953,"corporation":false,"usgs":false,"family":"Jones","given":"Leslie","affiliations":[],"preferred":false,"id":819200,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"D’Angelo, Vincent S. 0000-0003-1244-8091 vdangelo@usgs.gov","orcid":"https://orcid.org/0000-0003-1244-8091","contributorId":224823,"corporation":false,"usgs":true,"family":"D’Angelo","given":"Vincent","email":"vdangelo@usgs.gov","middleInitial":"S.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":819036,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Whiteley, Andrew R.","contributorId":150155,"corporation":false,"usgs":false,"family":"Whiteley","given":"Andrew","email":"","middleInitial":"R.","affiliations":[{"id":6932,"text":"University of Massachusetts, Amherst","active":true,"usgs":false}],"preferred":false,"id":819037,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hubblewhite, Mark","contributorId":260878,"corporation":false,"usgs":false,"family":"Hubblewhite","given":"Mark","email":"","affiliations":[{"id":36523,"text":"University of Montana","active":true,"usgs":false}],"preferred":false,"id":819038,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70216733,"text":"70216733 - 2021 - Small mammal responses to wetland restoration in the Greater Everglades ecosystem","interactions":[],"lastModifiedDate":"2021-04-08T14:17:17.479018","indexId":"70216733","displayToPublicDate":"2020-11-22T07:56:49","publicationYear":"2021","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":"Small mammal responses to wetland restoration in the Greater Everglades ecosystem","docAbstract":"Wetlands have experienced dramatic losses in extent around the world, disrupting ecosystem function, habitat, and biodiversity. In Florida’s Greater Everglades, a massive restoration effort costing billions of dollars and spanning multiple decades is underway. As Everglades restoration is implemented in incremental projects, scientists and planners monitor the outcomes of projects. In this study, we evaluated the progress of a restoration project in the southwestern Everglades. We aimed to determine whether the presence and density of small mammals differed between areas with hydrologic restoration of the ecosystem and areas without restoration. Our three focal species were: marsh rice rat (Oryzomys palustris), hispid cotton rat (Sigmodon hispidus), and cotton mouse (Peromyscus gossypinus). Using spatially explicit capture‐recapture models, we found greater densities of cotton mouse in restored habitat and lower densities of hispid cotton rat in sites with higher water levels. Additionally, we found an increase in the presence of the marsh rice rat in restored areas compared to unrestored, but captures were too low to reliably assess significance. Our study provides evidence that ongoing restoration in the southwestern Everglades is already impacting the small mammal community.
","language":"English","publisher":"Wiley","doi":"10.1111/rec.13332","usgsCitation":"Romanach, S., D’Acunto, L., Chapman, J., and Hanson, M., 2021, Small mammal responses to wetland restoration in the Greater Everglades ecosystem: Restoration Ecology, v. 29, no. 3, e13332, 9 p., https://doi.org/10.1111/rec.13332.","productDescription":"e13332, 9 p.","ipdsId":"IP-114410","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":454216,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/rec.13332","text":"Publisher Index Page"},{"id":436633,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9BWA7RD","text":"USGS data release","linkHelpText":"Small mammal captures at the Picayune Strand State Forest, October 2014 - April 2016"},{"id":380947,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Greater Everglades area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.97448730468749,\n 25.035838555635017\n ],\n [\n -79.903564453125,\n 25.035838555635017\n ],\n [\n -79.903564453125,\n 26.59343927024179\n ],\n [\n -81.97448730468749,\n 26.59343927024179\n ],\n [\n -81.97448730468749,\n 25.035838555635017\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"29","issue":"3","noUsgsAuthors":false,"publicationDate":"2020-12-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Romanach, Stephanie 0000-0003-0271-7825","orcid":"https://orcid.org/0000-0003-0271-7825","contributorId":220761,"corporation":false,"usgs":true,"family":"Romanach","given":"Stephanie","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":806009,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"D’Acunto, Laura 0000-0001-6227-0143","orcid":"https://orcid.org/0000-0001-6227-0143","contributorId":215343,"corporation":false,"usgs":true,"family":"D’Acunto","given":"Laura","email":"","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":806010,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chapman, Julia","contributorId":245353,"corporation":false,"usgs":false,"family":"Chapman","given":"Julia","affiliations":[],"preferred":false,"id":806011,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hanson, Matthew R 0000-0002-2859-3878","orcid":"https://orcid.org/0000-0002-2859-3878","contributorId":245354,"corporation":false,"usgs":false,"family":"Hanson","given":"Matthew R","affiliations":[],"preferred":false,"id":806012,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70216934,"text":"70216934 - 2021 - Evaluation of a roughness length parametrization accounting for wind–wave alignment in a coupled atmosphere–wave model","interactions":[],"lastModifiedDate":"2021-03-05T21:07:22.044536","indexId":"70216934","displayToPublicDate":"2020-11-21T12:54:49","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7443,"text":"Quarterly Journal of the Royal Meteorological Society","active":true,"publicationSubtype":{"id":10}},"title":"Evaluation of a roughness length parametrization accounting for wind–wave alignment in a coupled atmosphere–wave model","docAbstract":"The importance of wind energy as an alternative energy source has increased over the latest years with more focus on offshore winds. A good estimation of the offshore winds is thus of major importance for this industry. Up to now the effect of the wind–wave (mis)alignment has not yet been taken into account in coupled atmosphere–wave models to study the vertical wind profile and power production estimations of offshore wind farms. In this study the roughness length parametrization of Drennan et al. in 2003, and its extension addressing the wind–wave (mis)alignment proposed by Porchetta et al. in 2019, are investigated in the Coupled Ocean–Atmosphere–Wave–Sediment Transport (COAWST) model. This study shows that the yearly mean wind estimation at hub height (100 m) is improved by the roughness length parametrization of Porchetta et al. compared to Drennan. This is mainly due to the increased roughness of the former parametrization compare to the latter, even in aligned wind–wave conditions. This difference in roughness is caused by the dataset used to obtain the constants, deep‐water conditions versus mixed offshore conditions. Moreover, the roughness length parametrization of Porchetta et al. performs better in two of three alignment categories. Furthermore, similar model performances are obtained if we exclude the wind directions from the wind shadow zone of the measurement mast or the wind directions from the recently built Alpha Ventus wind farm, which is in close vicinity of the measurement mast. Investigating different wind conditions shows that the new roughness length parametrization of Porchetta et al. performs best for both offshore and onshore winds. Additionally, we show that the coupled model estimations of the vertical wind are only slightly affected by significant wave height estimations. Similar model performances for different accuracies of significant wave height estimations are presented. One exception is the perpendicular alignment category where the new roughness length of Porchetta et al. outperforms the roughness length of Drennan when investigating the wind estimations related to significant wave heights with a higher accuracy. The roughness length parametrization of Porchetta et al. reduced the power production overestimation of the coupled model from 5.7 to 2.8%. We also show that the standalone atmospheric model including the roughness length of Charnock in 1955 has a degraded performance compared to the coupled model including the roughness length parametrization of Porchetta et al. for yearly average wind profiles.
","language":"English","publisher":"Royal Meteorological Society","doi":"10.1002/qj.3948","usgsCitation":"Porchetta, S., Temel, O., Warner, J., Munoz-Esparza, J., Monbaliu, J., van Beeck, J., and van Lipzig, N., 2021, Evaluation of a roughness length parametrization accounting for wind–wave alignment in a coupled atmosphere–wave model: Quarterly Journal of the Royal Meteorological Society, v. 147, no. 735, p. 825-846, https://doi.org/10.1002/qj.3948.","productDescription":"22 p.","startPage":"825","endPage":"846","ipdsId":"IP-117950","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":454221,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://lirias.kuleuven.be/bitstream/123456789/685815/2/COAWST_QJRMetS_rkul.docx","text":"External Repository"},{"id":381447,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"147","issue":"735","noUsgsAuthors":false,"publicationDate":"2020-12-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Porchetta, Sara","contributorId":245775,"corporation":false,"usgs":false,"family":"Porchetta","given":"Sara","email":"","affiliations":[{"id":49315,"text":"KU Leuven, Department Earth and Environmental Sciences, Leuven, Belgium","active":true,"usgs":false}],"preferred":false,"id":807016,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Temel, O.","contributorId":245776,"corporation":false,"usgs":false,"family":"Temel","given":"O.","email":"","affiliations":[{"id":49316,"text":"Royal Observatory of Belgium, Brussels, Belgium","active":true,"usgs":false}],"preferred":false,"id":807017,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Warner, John C. 0000-0002-3734-8903 jcwarner@usgs.gov","orcid":"https://orcid.org/0000-0002-3734-8903","contributorId":2681,"corporation":false,"usgs":true,"family":"Warner","given":"John C.","email":"jcwarner@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":807018,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Munoz-Esparza, J.C.","contributorId":245777,"corporation":false,"usgs":false,"family":"Munoz-Esparza","given":"J.C.","email":"","affiliations":[{"id":16785,"text":"National Center for Atmospheric Research, Boulder, CO","active":true,"usgs":false}],"preferred":false,"id":807019,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Monbaliu, J","contributorId":245778,"corporation":false,"usgs":false,"family":"Monbaliu","given":"J","email":"","affiliations":[{"id":49317,"text":"KULeuven, Department of Civil Engineering, Leuven, Belgium","active":true,"usgs":false}],"preferred":false,"id":807020,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"van Beeck, J.","contributorId":245779,"corporation":false,"usgs":false,"family":"van Beeck","given":"J.","email":"","affiliations":[{"id":49319,"text":"KULeuven, Department Earth and Environmental Sciences, Leuven, Belgium","active":true,"usgs":false}],"preferred":false,"id":807021,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"van Lipzig, N.","contributorId":245780,"corporation":false,"usgs":false,"family":"van Lipzig","given":"N.","email":"","affiliations":[{"id":49321,"text":"von Karman Institute for Fluid Dynamics, Sint-Genesius-Rode, Belgium","active":true,"usgs":false}],"preferred":false,"id":807022,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70219218,"text":"70219218 - 2021 - Variable seepage meter efficiency in high-permeability settings","interactions":[],"lastModifiedDate":"2021-04-01T11:25:55.835244","indexId":"70219218","displayToPublicDate":"2020-11-21T06:47:55","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3709,"text":"Water","active":true,"publicationSubtype":{"id":10}},"title":"Variable seepage meter efficiency in high-permeability settings","docAbstract":"The efficiency of seepage meters, long considered a fixed property associated with the meter design, is not constant in highly permeable sediments. Instead, efficiency varies substantially with seepage bag fullness, duration of bag attachment, depth of meter insertion into the sediments, and seepage velocity. Tests conducted in a seepage test tank filled with isotropic sand with a hydraulic conductivity of about 60 m/d indicate that seepage meter efficiency varies widely and decreases unpredictably when the volume of the seepage bag is greater than about 65 to 70 percent full or less than about 15 to 20 percent full. Seepage generally decreases with duration of bag attachment even when operated in the mid-range of bag fullness. Stopping flow through the seepage meter during bag attachment or removal also results in a decrease in meter efficiency. Numerical modeling indicates efficiency is inversely related to hydraulic conductivity in highly permeable sediments. An efficiency close to 1 for a meter installed in sediment with a hydraulic conductivity of 1 m/d decreases to about 60 and then 10 percent when hydraulic conductivity is increased to 10 and 100 m/d, respectively. These large efficiency reductions apply only to high-permeability settings, such as wave- or tidally washed coarse sand or gravel, or fluvial settings with an actively mobile sand or gravel bed, where low resistance to flow through the porous media allows bypass flow around the seepage cylinder to readily occur. In more typical settings, much greater resistance to bypass flow suppresses small changes in meter resistance during inflation or deflation of seepage bags.
","language":"English","publisher":"MPDI","doi":"10.3390/w12113267","usgsCitation":"Rosenberry, D.O., Nieto-Lopez, J.M., Webb, R.M., and Muller, S., 2021, Variable seepage meter efficiency in high-permeability settings: Water, v. 12, no. 11, 3267, 22 p., https://doi.org/10.3390/w12113267.","productDescription":"3267, 22 p.","ipdsId":"IP-119819","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":454229,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/w12113267","text":"Publisher Index Page"},{"id":436637,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P93N8B2N","text":"USGS data release","linkHelpText":"Webb and Rosenberry, 2020, MODFLOW 2005 and MODPATH 5 model data sets used to evaluate seepage-meter efficiency in high-permeability settings"},{"id":436636,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P93N8B2N","text":"USGS data release","linkHelpText":"Webb and Rosenberry, 2020, MODFLOW 2005 and MODPATH 5 model data sets used to evaluate seepage-meter efficiency in high-permeability settings"},{"id":436635,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9SO2FVM","text":"USGS data release","linkHelpText":"Seepage meter efficiency in highly permeable settings source data (2020)"},{"id":436634,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9SO2FVM","text":"USGS data release","linkHelpText":"Seepage meter efficiency in highly permeable settings source data (2020)"},{"id":384775,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"12","issue":"11","noUsgsAuthors":false,"publicationDate":"2020-11-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Rosenberry, Donald O. 0000-0003-0681-5641 rosenber@usgs.gov","orcid":"https://orcid.org/0000-0003-0681-5641","contributorId":1312,"corporation":false,"usgs":true,"family":"Rosenberry","given":"Donald","email":"rosenber@usgs.gov","middleInitial":"O.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":813261,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nieto-Lopez, Jose M 0000-0002-2596-6368","orcid":"https://orcid.org/0000-0002-2596-6368","contributorId":256817,"corporation":false,"usgs":false,"family":"Nieto-Lopez","given":"Jose","email":"","middleInitial":"M","affiliations":[{"id":51863,"text":"University of Malaga","active":true,"usgs":false}],"preferred":false,"id":813262,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Webb, Richard M. 0000-0001-9531-2207 rmwebb@usgs.gov","orcid":"https://orcid.org/0000-0001-9531-2207","contributorId":1570,"corporation":false,"usgs":true,"family":"Webb","given":"Richard","email":"rmwebb@usgs.gov","middleInitial":"M.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":813263,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Muller, Sascha","contributorId":256818,"corporation":false,"usgs":false,"family":"Muller","given":"Sascha","email":"","affiliations":[{"id":12672,"text":"University of Copenhagen","active":true,"usgs":false}],"preferred":false,"id":813264,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70216564,"text":"70216564 - 2021 - Systematic characterization of morphotectonic variability along the Cascadia convergent margin: Implications for shallow megathrust behavior and tsunami hazards","interactions":[],"lastModifiedDate":"2021-02-04T00:04:42.827309","indexId":"70216564","displayToPublicDate":"2020-11-20T09:17:04","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1820,"text":"Geosphere","active":true,"publicationSubtype":{"id":10}},"title":"Systematic characterization of morphotectonic variability along the Cascadia convergent margin: Implications for shallow megathrust behavior and tsunami hazards","docAbstract":"Studies of recent destructive megathrust earthquakes and tsunamis along subduction margins in Japan, Sumatra, and Chile have linked forearc morphology and structure to megathrust behavior. This connection is based on the idea that spatial variations in the frictional behavior of the megathrust influence the tectono-morphological evolution of the upper plate. Here we present a comprehensive examination of the tectonic geomorphology, outer wedge taper, and structural vergence along the marine forearc of the Cascadia subduction zone (offshore northwestern North America). The goal is to better understand geologic controls on outer wedge strength and segmentation at spatial scales equivalent to rupture lengths of large earthquakes (≥M 6.7), and to examine potential linkages with shallow megathrust behavior.
We use cross-margin profiles, spaced 25 km apart, to characterize along-strike variation in outer wedge width, steepness, and structural vergence (measured between the toe and the outer arc high). The width of the outer wedge varies between 17 and 93 km, and the steepness ranges from 0.9° to 6.5°. Hierarchical cluster analysis of outer wedge width and steepness reveals four distinct regions that also display unique patterns of structural vergence and shape of the wedge: Vancouver Island, British Columbia, Canada (average width, linear wedge, seaward and mixed vergence); Washington, USA (higher width, concave wedge, landward and mixed vergence); northern and central Oregon, USA (average width, linear and convex wedge, mixed and seaward vergence); and southern Oregon and northern California, USA (lower width, convex wedge, seaward and mixed vergence). Variability in outer wedge morphology and structure is broadly associated with along-strike megathrust segmentation inferred from differences in oceanic asthenospheric velocities, patterns of episodic tremor and slow slip, GPS models of plate locking, and the distribution of seismicity near the plate interface. In more detail, our results appear to delineate the extent, geometry, and lithology of dynamic and static backstops along the margin. Varying backstop configurations along the Cascadia margin are interpreted to represent material-strength contrasts within the wedge that appear to regulate the along- and across-strike taper and structural vergence in the outer wedge. We argue that the morphotectonic variability in the outer wedge may reflect spatial variations in shallow megathrust behavior occurring over roughly the last few million years. Comparing outer wedge taper along the Cascadia margin to a global compilation suggests that observations in the global catalog are not accurately representing the range of heterogeneity within individual margins and highlights the need for detailed margin-wide morphotectonic analyses of subduction zones worldwide.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/GES02178.1","usgsCitation":"Watt, J., and Brothers, D.S., 2021, Systematic characterization of morphotectonic variability along the Cascadia convergent margin: Implications for shallow megathrust behavior and tsunami hazards: Geosphere, v. 17, no. 1, p. 95-117, https://doi.org/10.1130/GES02178.1.","productDescription":"19 p.","startPage":"95","endPage":"117","ipdsId":"IP-109931","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":454235,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/ges02178.1","text":"Publisher Index Page"},{"id":380781,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"British Columbia, California, Oregon, Washington","otherGeospatial":"Cascadia subduction zone","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.01367187499999,\n 40.195659093364654\n ],\n [\n -123.50830078125,\n 41.623655390686395\n ],\n [\n -123.662109375,\n 44.6061127451739\n ],\n [\n -123.662109375,\n 47.100044694025215\n ],\n [\n -123.11279296875001,\n 48.69096039092549\n ],\n [\n -128.1005859375,\n 51.248163159055906\n ],\n [\n -128.84765625,\n 50.999928855859636\n ],\n [\n -127.46337890625001,\n 40.97989806962013\n ],\n [\n -126.03515625,\n 39.605688178320804\n ],\n [\n -124.01367187499999,\n 40.195659093364654\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"17","issue":"1","noUsgsAuthors":false,"publicationDate":"2020-11-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Watt, Janet 0000-0002-4759-3814","orcid":"https://orcid.org/0000-0002-4759-3814","contributorId":221271,"corporation":false,"usgs":true,"family":"Watt","given":"Janet","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":805621,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brothers, Daniel S. 0000-0001-7702-157X dbrothers@usgs.gov","orcid":"https://orcid.org/0000-0001-7702-157X","contributorId":167089,"corporation":false,"usgs":true,"family":"Brothers","given":"Daniel","email":"dbrothers@usgs.gov","middleInitial":"S.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":805622,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70227051,"text":"70227051 - 2021 - Suspended-sediment Flux in the San Francisco Estuary; Part II: the Impact of the 2013–2016 California Drought and Controls on Sediment Flux","interactions":[],"lastModifiedDate":"2021-12-28T14:48:59.650241","indexId":"70227051","displayToPublicDate":"2020-11-20T08:46:39","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1584,"text":"Estuaries and Coasts","active":true,"publicationSubtype":{"id":10}},"title":"Suspended-sediment Flux in the San Francisco Estuary; Part II: the Impact of the 2013–2016 California Drought and Controls on Sediment Flux","docAbstract":"Recent modeling has demonstrated that sediment supply is one of the primary environmental variables that will determine the sustainability of San Francisco Estuary tidal marshes over the next century as sea level rises. Therefore, understanding the environmental controls on sediment flux within the San Francisco Estuary is crucial for optimal planning and management of tidal marsh restoration. Herein, we present suspended-sediment flux estimates from water year (WY) 2009–2016 from the San Francisco Estuary to investigate the environmental controls and impact of the record 2013–2016 California drought. During the recent drought, sediment flux into Lower South Bay, the southernmost subembayment of the San Francisco Estuary, increased by 345% from 114 kt/year from WY 2009 to 2011 to 508 kt/year from WY 2014 to 2016, while local tributary sediment flux declined from 209 to 51 kt/year. Total annual sediment flux from WY 2009 to 2011 and 2014 to 2016 can be predicted by total annual freshwater inflow from the Sacramento-San Joaquin Delta (R2 = 0.83, p < 0.01), the primary source of freshwater input into the San Francisco Estuary. The volume of freshwater inflow from the Sacramento-San Joaquin Delta is hypothesized to affect shoal-to-channel density gradients that affect sediment flux from broad, typically more saline and turbid shoals, to the main tidal-channel seaward of Lower South Bay. During the drought, freshwater inflow from the Sacramento-San Joaquin Delta decreased, and replacement of typically more saline shoal water was reduced. As a result, landward-increasing cross-channel density gradients enhanced shoal-to-channel advective flux that increased sediment available for tidal dispersion and drove an increase in net-landward sediment flux into Lower South Bay.
Geologists and petroleum engineers have struggled to identify the mechanisms that drive productivity in horizontal hydraulically fractured oil wells. The machine learning algorithms of Random Forest (RF), gradient boosting trees (GBT) and extreme gradient boosting (XGBoost) were applied to a dataset containing 7311 horizontal hydraulically fractured wells drilled into the middle member of the Bakken Formation from 2010 through 2017. The initial goal is to use these data‐driven machine learning algorithms to identify the most important explanatory predictors of well productivity within nine subareas and the composite area. Predictor variables representing initial gas production, the initial 180‐day water cut, and vertical depth vary spatially and are identified with geologically favorable areas. Well‐completion predictors include the well lateral length, number of fracture stages, volume of proppant per stage, and the volume of injected fluids per stage. The performance of methods is compared based on a common test sample. The analysis then examines the comparative predictive performance of the three algorithms for 1330 wells that had initiated production after the initial 7311 well sample had been producing. The computations of predictor importance identified the initial 180‐day water cut and the 30‐day initial gas production predictors as having a dominant influence in most subareas and for the composite area. The relative importance of well completion predictor variables, that is, the number of fracture stages per well, volume of injected proppant per stage, volume of injected fluids per stage, and lateral length, varied considerably across the subareas. For the common test or holdout sample, the models calibrated with the XGBoost algorithm had superior predictive power. The predictive power of all the algorithms trained on the data from the original sample suffered some loss when tested with a sample of wells that had started production after the end of that period. Implications of the empirical findings and strategies to mitigate loss of predictive power are discussed in the concluding section.