{"pageNumber":"192","pageRowStart":"4775","pageSize":"25","recordCount":46670,"records":[{"id":70222117,"text":"70222117 - 2021 - Diplotriaena obtusa (Nematoda: Diplotriaenidae) from barn swallows (Hirundo rustica) and cliff swallows (Petrochelidon pyrrhonota) collected during mortality events in the Upper Midwest, USA","interactions":[],"lastModifiedDate":"2021-09-09T16:41:58.050387","indexId":"70222117","displayToPublicDate":"2021-07-29T11:12:11","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2414,"text":"Journal of Parasitology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Diplotriaena obtusa (Nematoda: Diplotriaenidae) from barn swallows (Hirundo rustica) and cliff swallows (Petrochelidon pyrrhonota) collected during mortality events in the Upper Midwest, USA","title":"Diplotriaena obtusa (Nematoda: Diplotriaenidae) from barn swallows (Hirundo rustica) and cliff swallows (Petrochelidon pyrrhonota) collected during mortality events in the Upper Midwest, USA","docAbstract":"

Several mortality events involving barn swallows (Hirundo rustica) and cliff swallows (Petrochelidon pyrrhonota) were reported in the Upper Midwestern states in 2017 and 2018. Barn swallow mortality followed unseasonal cold snaps, with the primary cause of death being emaciation with concurrent air sac nematodiasis. Lesions in cliff swallows were consistent with blunt force trauma from suspected car impacts. Examination of air sac nematodes from both bird species revealed morphological characters consistent with Diplotriaena obtusa. Sequence analysis of the partial 18S rRNA gene indicated the samples clustered with other species in the genus Diplotriaena. These nematodes provide a link between morphological specimens and DNA sequence data for D. obtusa.

","language":"English","publisher":"American Society of Parasitologists","doi":"10.1645/19-76","usgsCitation":"Michalski, M., Kadolph, E., Roderick, C., Lankton, J.S., and Cole, R.A., 2021, Diplotriaena obtusa (Nematoda: Diplotriaenidae) from barn swallows (Hirundo rustica) and cliff swallows (Petrochelidon pyrrhonota) collected during mortality events in the Upper Midwest, USA: Journal of Parasitology, v. 107, no. 4, p. 593-599, https://doi.org/10.1645/19-76.","productDescription":"7 p.","startPage":"593","endPage":"599","ipdsId":"IP-107110","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":451349,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1645/19-76","text":"Publisher Index Page"},{"id":389006,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Illinois, Minnesota, Nebraska, South Dakota","city":"Cold Spring, Sioux Falls","otherGeospatial":"Grand Lake, Lewis and Clark State Recreation Area, Pleasant Valley Township","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -97.60348320007324,\n 42.83015652099459\n ],\n [\n -97.56580352783203,\n 42.83015652099459\n ],\n [\n -97.56580352783203,\n 42.84198920544056\n ],\n [\n -97.60348320007324,\n 42.84198920544056\n ],\n [\n -97.60348320007324,\n 42.83015652099459\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -96.92550659179688,\n 43.35214549645439\n ],\n [\n -96.70852661132812,\n 43.35214549645439\n ],\n [\n -96.70852661132812,\n 43.511708955963776\n ],\n [\n -96.92550659179688,\n 43.511708955963776\n ],\n [\n -96.92550659179688,\n 43.35214549645439\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -90.06900787353516,\n 42.194951362905265\n ],\n [\n -89.9948501586914,\n 42.194951362905265\n ],\n [\n -89.9948501586914,\n 42.24808928105648\n ],\n [\n -90.06900787353516,\n 42.24808928105648\n ],\n [\n -90.06900787353516,\n 42.194951362905265\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -94.4601058959961,\n 45.39820890405686\n ],\n [\n -94.30492401123047,\n 45.39820890405686\n ],\n [\n -94.30492401123047,\n 45.47048444989679\n ],\n [\n -94.4601058959961,\n 45.47048444989679\n ],\n [\n -94.4601058959961,\n 45.39820890405686\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"107","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Michalski, Michelle","contributorId":261249,"corporation":false,"usgs":false,"family":"Michalski","given":"Michelle","email":"","affiliations":[{"id":52783,"text":"University WI Oshkosh","active":true,"usgs":false}],"preferred":false,"id":822878,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kadolph, Emily","contributorId":261250,"corporation":false,"usgs":false,"family":"Kadolph","given":"Emily","email":"","affiliations":[{"id":52783,"text":"University WI Oshkosh","active":true,"usgs":false}],"preferred":false,"id":822879,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Roderick, Constance 0000-0001-8330-8024","orcid":"https://orcid.org/0000-0001-8330-8024","contributorId":215346,"corporation":false,"usgs":true,"family":"Roderick","given":"Constance","email":"","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":822880,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lankton, Julia S. 0000-0002-6843-4388 jlankton@usgs.gov","orcid":"https://orcid.org/0000-0002-6843-4388","contributorId":5888,"corporation":false,"usgs":true,"family":"Lankton","given":"Julia","email":"jlankton@usgs.gov","middleInitial":"S.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":822881,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cole, Rebecca A. 0000-0003-2923-1622 rcole@usgs.gov","orcid":"https://orcid.org/0000-0003-2923-1622","contributorId":2873,"corporation":false,"usgs":true,"family":"Cole","given":"Rebecca","email":"rcole@usgs.gov","middleInitial":"A.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":819590,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70221754,"text":"70221754 - 2021 - Using the DRCOG 2018 pilot land use land cover data to predict urban air temperature in the Denver metro area","interactions":[],"lastModifiedDate":"2021-09-15T15:42:12.114323","indexId":"70221754","displayToPublicDate":"2021-07-29T10:40:02","publicationYear":"2021","noYear":false,"publicationType":{"id":25,"text":"Newsletter"},"publicationSubtype":{"id":30,"text":"Newsletter"},"seriesTitle":{"id":9345,"text":"Denver Regional Data Consortium Newsletter","active":true,"publicationSubtype":{"id":30}},"title":"Using the DRCOG 2018 pilot land use land cover data to predict urban air temperature in the Denver metro area","docAbstract":"

No abstract available.

","language":"English","publisher":"Denver Regional Council of Governments","usgsCitation":"Ibsen, P.C., 2021, Using the DRCOG 2018 pilot land use land cover data to predict urban air temperature in the Denver metro area: Denver Regional Data Consortium Newsletter, 2 p.","productDescription":"2 p.","ipdsId":"IP-130771","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":389269,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":389268,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://drcog.org/services-and-resources/data-maps-and-modeling/regional-land-use-land-cover-project"}],"country":"United States","state":"Colorado","city":"Denver","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -105.28472900390625,\n 39.42770738465604\n ],\n [\n -104.57199096679688,\n 39.42770738465604\n ],\n [\n -104.57199096679688,\n 40.042334918180536\n ],\n [\n -105.28472900390625,\n 40.042334918180536\n ],\n [\n -105.28472900390625,\n 39.42770738465604\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Ibsen, Peter Christian 0000-0002-3436-9100","orcid":"https://orcid.org/0000-0002-3436-9100","contributorId":260735,"corporation":false,"usgs":true,"family":"Ibsen","given":"Peter","email":"","middleInitial":"Christian","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":818627,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70224300,"text":"70224300 - 2021 - FLUXNET-CH4: A global, multi-ecosystem database and analysis of methane seasonality from freshwater wetlands","interactions":[],"lastModifiedDate":"2021-09-21T15:05:21.492772","indexId":"70224300","displayToPublicDate":"2021-07-29T09:56:48","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1426,"text":"Earth System Science Data","active":true,"publicationSubtype":{"id":10}},"displayTitle":"FLUXNET-CH4: A global, multi-ecosystem database and analysis of methane seasonality from freshwater wetlands","title":"FLUXNET-CH4: A global, multi-ecosystem database and analysis of methane seasonality from freshwater wetlands","docAbstract":"

Methane (CH4) emissions from natural landscapes constitute roughly half of global CH4 contributions to the atmosphere, yet large uncertainties remain in the absolute magnitude and the seasonality of emission quantities and drivers. Eddy covariance (EC) measurements of CH4 flux are ideal for constraining ecosystem-scale CH4 emissions due to quasi-continuous and high-temporal-resolution CH4 flux measurements, coincident carbon dioxide, water, and energy flux measurements, lack of ecosystem disturbance, and increased availability of datasets over the last decade. Here, we (1) describe the newly published dataset, FLUXNET-CH4 Version 1.0, the first open-source global dataset of CH4 EC measurements (available at https://fluxnet.org/data/fluxnet-ch4-community-product/, last access: 7 April 2021). FLUXNET-CH4 includes half-hourly and daily gap-filled and non-gap-filled aggregated CH4 fluxes and meteorological data from 79 sites globally: 42 freshwater wetlands, 6 brackish and saline wetlands, 7 formerly drained ecosystems, 7 rice paddy sites, 2 lakes, and 15 uplands. Then, we (2) evaluate FLUXNET-CH4 representativeness for freshwater wetland coverage globally because the majority of sites in FLUXNET-CH4 Version 1.0 are freshwater wetlands which are a substantial source of total atmospheric CH4 emissions; and (3) we provide the first global estimates of the seasonal variability and seasonality predictors of freshwater wetland CH4 fluxes. Our representativeness analysis suggests that the freshwater wetland sites in the dataset cover global wetland bioclimatic attributes (encompassing energy, moisture, and vegetation-related parameters) in arctic, boreal, and temperate regions but only sparsely cover humid tropical regions. Seasonality metrics of wetland CH4 emissions vary considerably across latitudinal bands. In freshwater wetlands (except those between 20∘ S to 20∘ N) the spring onset of elevated CH4 emissions starts 3 d earlier, and the CH4 emission season lasts 4 d longer, for each degree Celsius increase in mean annual air temperature. On average, the spring onset of increasing CH4 emissions lags behind soil warming by 1 month, with very few sites experiencing increased CH4 emissions prior to the onset of soil warming. In contrast, roughly half of these sites experience the spring onset of rising CH4 emissions prior to the spring increase in gross primary productivity (GPP). The timing of peak summer CH4 emissions does not correlate with the timing for either peak summer temperature or peak GPP. Our results provide seasonality parameters for CH4 modeling and highlight seasonality metrics that cannot be predicted by temperature or GPP (i.e., seasonality of CH4 peak). FLUXNET-CH4 is a powerful new resource for diagnosing and understanding the role of terrestrial ecosystems and climate drivers in the global CH4 cycle, and future additions of sites in tropical ecosystems and site years of data collection will provide added value to this database. All seasonality parameters are available at https://doi.org/10.5281/zenodo.4672601 (Delwiche et al., 2021). Additionally, raw FLUXNET-CH4 data used to extract seasonality parameters can be downloaded from https://fluxnet.org/data/fluxnet-ch4-community-product/ (last access: 7 April 2021), and a complete list of the 79 individual site data DOIs is provided in Table 2 of this paper.

","language":"English","publisher":"Copernicus Publications","doi":"10.5194/essd-13-3607-2021","usgsCitation":"Delwiche, K.B., Knox, S., Malhotra, A., Fluet-Chouinard, E., McNicol, G., Feron, S., Ouyang, Z., Papale, D., Trotta, C., Canfora, E., Cheah, Y., Christianson, D., Alberto, M.C., Alekseychik, P., Aurela, M., Baldocchi, D., Bansal, S., Billesbach, D.P., Bohrer, G., Bracho, R., Buchmann, N., Campbell, D.I., Celis, G., Chen, W., Chen, J., Chu, H., Dalmagro, H.J., Dengel, S., Desai, A.R., Detto, M., Dolman, H., Eichelmann, E., Euskirchen, E.S., Famulari, D., Fuchs, K., Goeckede, M., Gogo, S., Gondwe, M., Goodrich, J.P., Gottschalk, P., Graham, S.L., Heimann, M., Helbig, M., Helfter, C., Hemes, K.S., Hirano, T., Hollinger, D., Hortnagl, L., Iwata, H., Jacotot, A., Jansen, J., Jurasinski, G., Kang, M., Kasak, K., King, J., Klatt, J., Koebsch, F., Krauss, K., Lai, D.Y., Lohila, A., Mammarella, I., Marchesini, L.B., Manca, G., Matthes, J.H., Maximov, T., Merbold, L., Mitra, B., Morin, T.H., Nemitz, E., Nilsson, M.B., Niu, S., Oechel, W.C., Oikawa, P.Y., Ono, K., Peichl, M., Peltola, O., Reba, M.L., Richardson, A.D., Riley, W., Runkle, B.R., Ryu, Y., Sachs, T., Sakabe, A., Sanchez, C.R., Schuur, E.A., Schafer, K.V., Sonnentag, O., Sparks, J.P., Stuart-Haëntjens, E., Sturtevant, C., Sullivan, R.C., Szutu, D., Thom, J.E., Torn, M.S., Tuittila, E., Turner, J., Ueyama, M., Valach, A.C., Vargas, R., Varlagin, A., Vazquez-Lule, A., Verfaillie, J.G., Vesala, T., Vourlitis, G.L., Ward, E., Wille, C., Wohlfahrt, G., Xhuan Wong, G., Zhang, Z., Zona, D., Windham-Myers, L., Poulter, B., and Jackson, R.B., 2021, FLUXNET-CH4: A global, multi-ecosystem database and analysis of methane seasonality from freshwater wetlands: Earth System Science Data, v. 13, p. 3607-3689, https://doi.org/10.5194/essd-13-3607-2021.","productDescription":"83 p.","startPage":"3607","endPage":"3689","ipdsId":"IP-122238","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":451358,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/essd-13-3607-2021","text":"Publisher Index Page"},{"id":389546,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"13","noUsgsAuthors":false,"publicationDate":"2021-07-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Delwiche, Kyle B.","contributorId":139866,"corporation":false,"usgs":false,"family":"Delwiche","given":"Kyle","email":"","middleInitial":"B.","affiliations":[{"id":13299,"text":"Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, MA","active":true,"usgs":false}],"preferred":false,"id":823506,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Knox, Sarah 0000-0003-2255-5835","orcid":"https://orcid.org/0000-0003-2255-5835","contributorId":167493,"corporation":false,"usgs":false,"family":"Knox","given":"Sarah","affiliations":[{"id":24725,"text":"Ecosystem Science Division, Department of Environmental Science","active":true,"usgs":false}],"preferred":false,"id":823507,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Malhotra, Avni 0000-0002-7850-6402","orcid":"https://orcid.org/0000-0002-7850-6402","contributorId":197909,"corporation":false,"usgs":false,"family":"Malhotra","given":"Avni","email":"","affiliations":[{"id":35065,"text":"Climate Change Science Institute and Environmental Sciences Division, Oak Ridge National Laboratory","active":true,"usgs":false}],"preferred":false,"id":823508,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fluet-Chouinard, Etienne","contributorId":217392,"corporation":false,"usgs":false,"family":"Fluet-Chouinard","given":"Etienne","email":"","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":823509,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McNicol, Gavin 0000-0002-6655-8045","orcid":"https://orcid.org/0000-0002-6655-8045","contributorId":260536,"corporation":false,"usgs":false,"family":"McNicol","given":"Gavin","email":"","affiliations":[],"preferred":false,"id":823510,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Feron, Sarah","contributorId":260553,"corporation":false,"usgs":false,"family":"Feron","given":"Sarah","email":"","affiliations":[],"preferred":false,"id":823511,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ouyang, Zutao","contributorId":260556,"corporation":false,"usgs":false,"family":"Ouyang","given":"Zutao","email":"","affiliations":[],"preferred":false,"id":823512,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Papale, Dario 0000-0001-5170-8648","orcid":"https://orcid.org/0000-0001-5170-8648","contributorId":217395,"corporation":false,"usgs":false,"family":"Papale","given":"Dario","email":"","affiliations":[{"id":39616,"text":"Università degli Studi della Tuscia","active":true,"usgs":false}],"preferred":false,"id":823513,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Trotta, Carlo 0000-0001-6377-0262","orcid":"https://orcid.org/0000-0001-6377-0262","contributorId":217399,"corporation":false,"usgs":false,"family":"Trotta","given":"Carlo","email":"","affiliations":[{"id":39616,"text":"Università degli Studi della Tuscia","active":true,"usgs":false}],"preferred":false,"id":823514,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Canfora, Eleonora","contributorId":265827,"corporation":false,"usgs":false,"family":"Canfora","given":"Eleonora","email":"","affiliations":[{"id":54808,"text":"euroMediterranean Center on Climate Change","active":true,"usgs":false}],"preferred":false,"id":823515,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Cheah, You-Wei","contributorId":265828,"corporation":false,"usgs":false,"family":"Cheah","given":"You-Wei","email":"","affiliations":[{"id":39617,"text":"Lawrence Berkeley National Lab","active":true,"usgs":false}],"preferred":false,"id":823516,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Christianson, Danielle","contributorId":265829,"corporation":false,"usgs":false,"family":"Christianson","given":"Danielle","email":"","affiliations":[{"id":39617,"text":"Lawrence Berkeley National Lab","active":true,"usgs":false}],"preferred":false,"id":823517,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Alberto, Ma. Carmelita R.","contributorId":265830,"corporation":false,"usgs":false,"family":"Alberto","given":"Ma.","email":"","middleInitial":"Carmelita R.","affiliations":[{"id":54809,"text":"International Rice Research Institute","active":true,"usgs":false}],"preferred":false,"id":823518,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Alekseychik, Pavel","contributorId":260558,"corporation":false,"usgs":false,"family":"Alekseychik","given":"Pavel","email":"","affiliations":[],"preferred":false,"id":823519,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Aurela, Mika 0000-0002-4046-7225","orcid":"https://orcid.org/0000-0002-4046-7225","contributorId":217400,"corporation":false,"usgs":false,"family":"Aurela","given":"Mika","email":"","affiliations":[{"id":39618,"text":"Finnish Meteorological Institute","active":true,"usgs":false}],"preferred":false,"id":823520,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Baldocchi, Dennis 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Nebraska-Lincoln","active":true,"usgs":false}],"preferred":false,"id":823523,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Bohrer, Gil 0000-0002-9209-9540","orcid":"https://orcid.org/0000-0002-9209-9540","contributorId":217401,"corporation":false,"usgs":false,"family":"Bohrer","given":"Gil","email":"","affiliations":[{"id":18155,"text":"The Ohio State University","active":true,"usgs":false}],"preferred":false,"id":823524,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Bracho, Rosvel","contributorId":178289,"corporation":false,"usgs":false,"family":"Bracho","given":"Rosvel","email":"","affiliations":[],"preferred":false,"id":823525,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Buchmann, Nina","contributorId":265832,"corporation":false,"usgs":false,"family":"Buchmann","given":"Nina","email":"","affiliations":[{"id":12483,"text":"ETH 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Earth System Processes Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":823617,"contributorType":{"id":1,"text":"Authors"},"rank":111},{"text":"Poulter, Benjamin 0000-0002-9493-8600","orcid":"https://orcid.org/0000-0002-9493-8600","contributorId":200477,"corporation":false,"usgs":false,"family":"Poulter","given":"Benjamin","email":"","affiliations":[],"preferred":false,"id":823618,"contributorType":{"id":1,"text":"Authors"},"rank":112},{"text":"Jackson, Robert B. 0000-0001-8846-7147","orcid":"https://orcid.org/0000-0001-8846-7147","contributorId":34252,"corporation":false,"usgs":false,"family":"Jackson","given":"Robert","email":"","middleInitial":"B.","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":823619,"contributorType":{"id":1,"text":"Authors"},"rank":113}]}} ,{"id":70236722,"text":"70236722 - 2021 - Late Holocene slip rate of the Mojave section of the San Andreas Fault near Palmdale, California","interactions":[],"lastModifiedDate":"2022-09-16T12:28:22.314471","indexId":"70236722","displayToPublicDate":"2021-07-29T07:25:02","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Late Holocene slip rate of the Mojave section of the San Andreas Fault near Palmdale, California","docAbstract":"

The geologic slip rate on the Mojave section of the San Andreas fault is poorly constrained, despite its importance for understanding earthquake hazard, apparent discrepancies between geologic and geodetic slip rates along this fault section, and long‐term fault interactions in southern California. Here, we use surficial geologic mapping, excavations, and radiocarbon and luminescence dating to quantify the displacements and ages of late Holocene landforms offset by the fault at three sites. At the Ranch Center site, the slip rate is determined using the base of a fan marking incision and deflection of an ephemeral channel. At the adjacent Key Slide site, the margin of a landslide deposited on indigenous fire hearths provides a minimum rate. At the X‐12 site, the slip rate is determined from a channel that incised into a broad fan surface, and is deflected and beheaded by the fault. We use maximum–minimum bounds on both the displacement and age of each offset feature to calculate slip rate for each site independently. Overlap of the three independent rate ranges yields a rate of 33–39 mm/yr over the last 3 ka, under the assumption that the sites share a common history, given their proximity. Considered in sequence, site‐level epistemic uncertainties in the data permit but do not require a rate increase since ∼1200 cal B.P. Modest rate changes can be explained by aleatory variability in earthquake timing and magnitude; larger changes could suggest a shared regional variation with the Garlock and other faults. The new late Holocene slip rates are consistent with geodetic model estimates that include a viscoelastic crust and earthquake cycle effects. The geologic slip rates also provide average slip over dozens of earthquake cycles—a key constraint for long‐term earthquake rupture forecasts.

","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120200278","usgsCitation":"Young, E., Cowgill, E., Scharer, K., Anderson-Merritt, E., Keen-Zebert, A., and Weldon, R.J., 2021, Late Holocene slip rate of the Mojave section of the San Andreas Fault near Palmdale, California: Bulletin of the Seismological Society of America, v. 111, no. 6, p. 3204-3225, https://doi.org/10.1785/0120200278.","productDescription":"22 p.","startPage":"3204","endPage":"3225","ipdsId":"IP-126803","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":406830,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","city":"Palmdale","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -118.97918701171876,\n 34.252676117101515\n ],\n [\n -117.333984375,\n 34.252676117101515\n ],\n [\n -117.333984375,\n 35.07046911981966\n ],\n [\n -118.97918701171876,\n 35.07046911981966\n ],\n [\n -118.97918701171876,\n 34.252676117101515\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"111","issue":"6","noUsgsAuthors":false,"publicationDate":"2021-06-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Young, Elaine","contributorId":296630,"corporation":false,"usgs":false,"family":"Young","given":"Elaine","email":"","affiliations":[{"id":12711,"text":"UC Davis","active":true,"usgs":false}],"preferred":false,"id":852009,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cowgill, Eric","contributorId":192850,"corporation":false,"usgs":false,"family":"Cowgill","given":"Eric","affiliations":[],"preferred":false,"id":852010,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Scharer, Katherine M. 0000-0003-2811-2496","orcid":"https://orcid.org/0000-0003-2811-2496","contributorId":217361,"corporation":false,"usgs":true,"family":"Scharer","given":"Katherine M.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":852011,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Anderson-Merritt, Emery","contributorId":296632,"corporation":false,"usgs":false,"family":"Anderson-Merritt","given":"Emery","email":"","affiliations":[{"id":12711,"text":"UC Davis","active":true,"usgs":false}],"preferred":false,"id":852012,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Keen-Zebert, Amanda","contributorId":224228,"corporation":false,"usgs":false,"family":"Keen-Zebert","given":"Amanda","email":"","affiliations":[{"id":40841,"text":"University of Nevada Reno / Desert Research Institute","active":true,"usgs":false}],"preferred":false,"id":852013,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Weldon, Ray J.","contributorId":175463,"corporation":false,"usgs":false,"family":"Weldon","given":"Ray","email":"","middleInitial":"J.","affiliations":[{"id":6604,"text":"University of Oregon","active":true,"usgs":false}],"preferred":false,"id":852014,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70236257,"text":"70236257 - 2021 - Pervasive changes in stream intermittency across the United States","interactions":[],"lastModifiedDate":"2022-08-31T12:19:33.492653","indexId":"70236257","displayToPublicDate":"2021-07-29T07:11:28","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1562,"text":"Environmental Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Pervasive changes in stream intermittency across the United States","docAbstract":"

Non-perennial streams are widespread, critical to ecosystems and society, and the subject of ongoing policy debate. Prior large-scale research on stream intermittency has been based on long-term averages, generally using annually aggregated data to characterize a highly variable process. As a result, it is not well understood if, how, or why the hydrology of non-perennial streams is changing. Here, we investigate trends and drivers of three intermittency signatures that describe the duration, timing, and dry-down period of stream intermittency across the continental United States (CONUS). Half of gages exhibited a significant trend through time in at least one of the three intermittency signatures, and changes in no-flow duration were most pervasive (41% of gages). Changes in intermittency were substantial for many streams, and 7% of gages exhibited changes in annual no-flow duration exceeding 100 days during the study period. Distinct regional patterns of change were evident, with widespread drying in southern CONUS and wetting in northern CONUS. These patterns are correlated with changes in aridity, though drivers of spatiotemporal variability were diverse across the three intermittency signatures. While the no-flow timing and duration were strongly related to climate, dry-down period was most strongly related to watershed land use and physiography. Our results indicate that non-perennial conditions are increasing in prevalence over much of CONUS and binary classifications of 'perennial' and 'non-perennial' are not an accurate reflection of this change. Water management and policy should reflect the changing nature and diverse drivers of changing intermittency both today and in the future.

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Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-5063","displayTitle":"Peak-Flow Variability, Peak-Flow Informational Needs, and Consideration of Regional Regression Analyses in Managing the Crest-Stage Gage Network in Montana","title":"Peak-flow variability, peak-flow informational needs, and consideration of regional regression analyses in managing the crest-stage gage network in Montana","docAbstract":"

The U.S. Geological Survey (USGS), in cooperation with the Montana Department of Transportation (MDT), has operated a crest-stage gage (CSG) network in Montana to collect peak-flow data since 1955. The CSG network is vital to collecting peak-flow data on small drainage basins that typically are not addressed by continuous streamflow operations. Discussions between USGS and MDT identified a need for evaluating the CSG network to allow for better decision making in the management of the network. The purpose of this report is to (1) generally describe peak-flow variability in Montana, (2) assess peak-flow informational needs relevant to MDT activities, and (3) consider the characteristics of the active CSG network in relation to addressing the informational needs. The evaluation of the CSG network is intended to assist in prioritization for discontinuation of CSGs and other activities involving changes to the CSG network.

Peak-flow variability was investigated by analysis of selected peak-flow characteristics of 659 unregulated streamgages in or near Montana. A generalized peak-flow variability index (PFVI) was developed to provide large-scale representation of peak-flow variability in Montana. For unregulated Montana streamgages, PFVI generally monotonically decreases with increasing drainage area, although there is somewhat large (but generally consistent) variability about the locally weighted scatterplot smooth line. Presumably, highly variable small-scale hydroclimatic processes are integrated with increasing drainage area such that variability in many hydrologic characteristics is reduced. PFVI also decreases with increasing mean basin elevation and mean annual precipitation. Presumably, higher elevation and wetter hydroclimatic settings in Montana contribute to reduced variability in hydrologic characteristics. Intuitively, PFVI might be expected to generally decrease with increasing years of record because the standard deviation might typically be expected to decrease with increasing sample size. However, relations among PFVI and years of record are more complex and variable than drainage area, elevation, and precipitation. PFVI variably increases from 10 to about 40 years of record and then generally monotonically decreases from about 40 to about 105 years of record. Relations among PFVI and the years of record might be confounded by effects of drainage area because streamgages with long periods of record (greater than about 60 years) generally have large drainage areas (greater than about 100 square miles).

The relations between PFVI and drainage area, mean basin elevation, mean annual precipitation, and years of record substantially differ among the eight hydrologic regions in Montana. As such, the PFVI relations were further investigated within each hydrologic region.

A major use of peak-flow information by MDT is for design of road and highway infrastructure, including bridges, culverts, and roadside drainage ditches. As such, basin characteristics (including drainage area, mean basin elevation, and mean annual precipitation) of the Montana streamgage network (735 regulated and unregulated streamgages) were statistically investigated in relation to basin characteristics of 12,639 road and stream intersections in Montana. Both regulated and unregulated streamgages were investigated because the road and stream intersections are on both regulated and unregulated streams. Exploratory analyses indicated that the various relations substantially differ among the hydrologic regions. As such, the relations between the Montana streamgage network and the road and stream intersections were further investigated within each hydrologic region.

An important objective of the CSG network is to provide data for developing regional regression equations (RREs) for estimating frequencies at ungaged sites in Montana. Various characteristics of the RREs substantially differ among the eight hydrologic regions in Montana. As such, the RRE characteristics were further investigated within each hydrologic region.

For each of the eight hydrologic regions, various characteristics of peak-flow variability, peak-flow informational needs, and regional regression analyses were investigated in detail. Possible shortcomings of the streamgage network in each hydrologic region are identified and possible future improvements to the CSG network are presented.

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\"}}]}","contact":"

Director, Wyoming-Montana Water Science Center
U.S. Geological Survey
3162 Bozeman Avenue
Helena, MT 59601

","tableOfContents":"","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2021-07-28","noUsgsAuthors":false,"publicationDate":"2021-07-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Sando, Steven K. 0000-0003-1206-1030","orcid":"https://orcid.org/0000-0003-1206-1030","contributorId":203451,"corporation":false,"usgs":true,"family":"Sando","given":"Steven","email":"","middleInitial":"K.","affiliations":[{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true}],"preferred":true,"id":819190,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70223765,"text":"70223765 - 2021 - The influence of subcolony-scale nesting habitat on the reproductive success of Adélie penguins","interactions":[],"lastModifiedDate":"2021-09-07T15:54:05.451384","indexId":"70223765","displayToPublicDate":"2021-07-28T10:43:38","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3358,"text":"Scientific Reports","active":true,"publicationSubtype":{"id":10}},"title":"The influence of subcolony-scale nesting habitat on the reproductive success of Adélie penguins","docAbstract":"

Group-size variation is common in colonially breeding species, including seabirds, whose breeding colonies can vary in size by several orders of magnitude. Seabirds are some of the most threatened marine taxa and understanding the drivers of colony size variation is more important than ever. Reproductive success is an important demographic parameter that can impact colony size, and it varies in association with a number of factors, including nesting habitat quality. Within colonies, seabirds often aggregate into distinct groups or subcolonies that may vary in quality. We used data from two colonies of Adélie penguins 73 km apart on Ross Island, Antarctica, one large and one small to investigate (1) How subcolony habitat characteristics influence reproductive success and (2) How these relationships differ at a small (Cape Royds) and large (Cape Crozier) colony with different terrain characteristics. Subcolonies were characterized using terrain attributes (elevation, slope aspect, slope steepness, wind shelter, flow accumulation), as well group characteristics (area/size, perimeter-to-area ratio, and proximity to nest predators). Reproductive success was higher and less variable at the larger colony while subcolony characteristics explained more of the variance in reproductive success at the small colony. The most important variable influencing subcolony quality at both colonies was perimeter-to-area ratio, likely reflecting the importance of nest predation by south polar skuas along subcolony edges. The small colony contained a higher proportion of edge nests thus higher potential impact from skua nest predation. Stochastic environmental events may facilitate smaller colonies becoming “trapped” by nest predation: a rapid decline in the number of breeding individuals may increase the proportion of edge nests, leading to higher relative nest predation and hindering population recovery. Several terrain covariates were retained in the final models but which variables, the shapes of the relationships, and importance varied between colonies.

","language":"English","publisher":"Nature Publications","doi":"10.1038/s41598-021-94861-7","usgsCitation":"Schmidt, A.E., Ballard, G., Lescroël, A., Dugger, K., Jongsomjit, D., Elrod, M.L., and Ainley, D., 2021, The influence of subcolony-scale nesting habitat on the reproductive success of Adélie penguins: Scientific Reports, v. 11, 15380, 15 p., https://doi.org/10.1038/s41598-021-94861-7.","productDescription":"15380, 15 p.","ipdsId":"IP-105335","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":451374,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-021-94861-7","text":"Publisher Index Page"},{"id":388881,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Antarctica, Cape Crozier, Cape Royds, Ross Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 160.1806640625,\n -78.56048828398782\n ],\n [\n 173.32031249999997,\n -78.56048828398782\n ],\n [\n 173.32031249999997,\n -75.28657817848102\n ],\n [\n 160.1806640625,\n -75.28657817848102\n ],\n [\n 160.1806640625,\n -78.56048828398782\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"11","noUsgsAuthors":false,"publicationDate":"2021-07-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Schmidt, Annie E.","contributorId":265338,"corporation":false,"usgs":false,"family":"Schmidt","given":"Annie","email":"","middleInitial":"E.","affiliations":[{"id":48619,"text":"pbcs","active":true,"usgs":false}],"preferred":false,"id":822578,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ballard, Grant","contributorId":265339,"corporation":false,"usgs":false,"family":"Ballard","given":"Grant","affiliations":[{"id":48619,"text":"pbcs","active":true,"usgs":false}],"preferred":false,"id":822579,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lescroël, Amélie","contributorId":265340,"corporation":false,"usgs":false,"family":"Lescroël","given":"Amélie","affiliations":[{"id":48619,"text":"pbcs","active":true,"usgs":false}],"preferred":false,"id":822580,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dugger, Katie M. 0000-0002-4148-246X cdugger@usgs.gov","orcid":"https://orcid.org/0000-0002-4148-246X","contributorId":4399,"corporation":false,"usgs":true,"family":"Dugger","given":"Katie","email":"cdugger@usgs.gov","middleInitial":"M.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":822577,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jongsomjit, Dennis","contributorId":265341,"corporation":false,"usgs":false,"family":"Jongsomjit","given":"Dennis","affiliations":[{"id":48619,"text":"pbcs","active":true,"usgs":false}],"preferred":false,"id":822581,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Elrod, Megan L.","contributorId":265342,"corporation":false,"usgs":false,"family":"Elrod","given":"Megan","email":"","middleInitial":"L.","affiliations":[{"id":48619,"text":"pbcs","active":true,"usgs":false}],"preferred":false,"id":822582,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ainley, David G.","contributorId":265343,"corporation":false,"usgs":false,"family":"Ainley","given":"David G.","affiliations":[],"preferred":false,"id":822583,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70224254,"text":"70224254 - 2021 - Why do my squiggles look funny? A gallery of compromised seismic signals","interactions":[],"lastModifiedDate":"2021-11-01T16:00:21.34454","indexId":"70224254","displayToPublicDate":"2021-07-28T07:29:38","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"Why do my squiggles look funny? A gallery of compromised seismic signals","docAbstract":"

Seismic instruments are highly sensitive and capable of recording a large range of different Earth signals. The high sensitivity of these instruments also makes them prone to various failures. Although many failures are very obvious, such as a dead channel, there are other more subtle failures that easily go unnoticed by both network operators and data users. This work documents several different types of failure modes in which the instrument is no longer faithfully recording ground‐motion data. Although some of these failure modes make the data completely unusable, there are also a number of failures in which the data can still be used for certain applications. Of course, the ideal situation is to identify as soon as possible when data become compromised and to have the network operator fix the station. However, knowing how the data became compromised can also help data users to identify if the data can still be used for their particular application. This work in no way attempts to exhaustively document recording failures but rather to communicate examples and equip the reader with ways of identifying failure modes.

","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220210094","usgsCitation":"Ringler, A.T., Mason, D.B., Laske, G., Storm, T., and Templeton, M., 2021, Why do my squiggles look funny? A gallery of compromised seismic signals: Seismological Research Letters, v. 92, no. 6, p. 3873-3886, https://doi.org/10.1785/0220210094.","productDescription":"14 p.","startPage":"3873","endPage":"3886","ipdsId":"IP-130410","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":389332,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"92","issue":"6","noUsgsAuthors":false,"publicationDate":"2021-07-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Ringler, Adam T. 0000-0002-9839-4188 aringler@usgs.gov","orcid":"https://orcid.org/0000-0002-9839-4188","contributorId":3946,"corporation":false,"usgs":true,"family":"Ringler","given":"Adam","email":"aringler@usgs.gov","middleInitial":"T.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":823363,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mason, David B. 0000-0003-0313-3370 dmason@usgs.gov","orcid":"https://orcid.org/0000-0003-0313-3370","contributorId":265781,"corporation":false,"usgs":true,"family":"Mason","given":"David","email":"dmason@usgs.gov","middleInitial":"B.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":823364,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Laske, G.","contributorId":265782,"corporation":false,"usgs":false,"family":"Laske","given":"G.","email":"","affiliations":[{"id":38724,"text":"Scripps Institution of Oceanography, University of California San Diego","active":true,"usgs":false}],"preferred":false,"id":823365,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Storm, Tyler 0000-0002-6787-9545 tstorm@usgs.gov","orcid":"https://orcid.org/0000-0002-6787-9545","contributorId":152165,"corporation":false,"usgs":true,"family":"Storm","given":"Tyler","email":"tstorm@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":823366,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Templeton, M.","contributorId":265783,"corporation":false,"usgs":false,"family":"Templeton","given":"M.","email":"","affiliations":[{"id":39228,"text":"Incorporated Research Institutions for Seismology","active":true,"usgs":false}],"preferred":false,"id":823367,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70223296,"text":"70223296 - 2021 - Comparison of aerial thermal infrared imagery and helicopter surveys of bison (Bison bison) in Grand Canyon National Park, USA","interactions":[],"lastModifiedDate":"2021-08-20T13:53:38.465029","indexId":"70223296","displayToPublicDate":"2021-07-27T08:51:16","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3380,"text":"Sensors","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Comparison of aerial thermal infrared imagery and helicopter surveys of bison (Bison bison) in Grand Canyon National Park, USA","title":"Comparison of aerial thermal infrared imagery and helicopter surveys of bison (Bison bison) in Grand Canyon National Park, USA","docAbstract":"Aerial thermal infrared (TIR) surveys are an attractive option for estimating abundances of large mammals inhabiting extensive and heterogenous terrain. Compared to standard helicopter or fixed-wing aerial surveys, TIR flights can be conducted at higher altitudes translating into greater spatial coverage and increased observer safety; however, monetary costs are much greater. Further, there is no consensus on whether TIR surveys offer improved detection. Consequently, we per-formed a study to compare results of a TIR and helicopter survey of bison (Bison bison) on the Powell Plateau in Grand Canyon National Park, USA. We also compared results of both surveys to esti-mates obtained using a larger dataset of bison helicopter detections along the entire North Rim of the Grand Canyon. Observers in the TIR survey counted fewer individual bison than helicopter ob-servers (101 to 127) and the TIR survey cost was 367% higher. Additionally, the TIR estimate was 18.8% lower than the estimate obtained using a larger dataset, while the comparative helicopter survey was 9.3% lower. Given the higher raw count, ostensibly more accurate estimates, and lower cost, we propose that helicopter surveys are currently the best choice for estimation and monitoring of bison abundance in Grand Canyon National Park.","language":"English","publisher":"MDPI","doi":"10.3390/s21155087","usgsCitation":"Hennig, J.D., Schoenecker, K., Terwilliger, M., Holm, G.W., and Laake, J.L., 2021, Comparison of aerial thermal infrared imagery and helicopter surveys of bison (Bison bison) in Grand Canyon National Park, USA: Sensors, v. 21, no. 15, 5087, 9 p., https://doi.org/10.3390/s21155087.","productDescription":"5087, 9 p.","ipdsId":"IP-129922","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":451392,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/s21155087","text":"Publisher Index Page"},{"id":436263,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9CXDC8V","text":"USGS data release","linkHelpText":"Detections of bison from helicopter and aerial thermal infrared imagery in Grand Canyon National Park, 2019-2021"},{"id":388230,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Grand Canyon National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.0380859375,\n 35.63051198300061\n ],\n [\n -111.22558593749999,\n 35.63051198300061\n ],\n [\n -111.22558593749999,\n 36.96744946416934\n ],\n [\n -114.0380859375,\n 36.96744946416934\n ],\n [\n -114.0380859375,\n 35.63051198300061\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"21","issue":"15","noUsgsAuthors":false,"publicationDate":"2021-07-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Hennig, Jacob Daniel 0000-0001-6450-6906","orcid":"https://orcid.org/0000-0001-6450-6906","contributorId":264526,"corporation":false,"usgs":true,"family":"Hennig","given":"Jacob","email":"","middleInitial":"Daniel","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":821636,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schoenecker, Kathryn A. 0000-0001-9906-911X","orcid":"https://orcid.org/0000-0001-9906-911X","contributorId":202531,"corporation":false,"usgs":true,"family":"Schoenecker","given":"Kathryn A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":821637,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Terwilliger, Miranda","contributorId":264527,"corporation":false,"usgs":false,"family":"Terwilliger","given":"Miranda","email":"","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":821638,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Holm, Gregory W","contributorId":264528,"corporation":false,"usgs":false,"family":"Holm","given":"Gregory","email":"","middleInitial":"W","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":821639,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Laake, Jeffrey L.","contributorId":83851,"corporation":false,"usgs":false,"family":"Laake","given":"Jeffrey","email":"","middleInitial":"L.","affiliations":[{"id":6578,"text":"National Marine Fisheries Service, Seattle, WA 98112, USA","active":true,"usgs":false}],"preferred":false,"id":821640,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70226979,"text":"70226979 - 2021 - Spectral damping scaling factors for horizontal components of ground motions from subduction earthquakes using NGA-Subduction data","interactions":[],"lastModifiedDate":"2021-12-23T13:24:13.864122","indexId":"70226979","displayToPublicDate":"2021-07-27T07:18:43","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1436,"text":"Earthquake Spectra","active":true,"publicationSubtype":{"id":10}},"title":"Spectral damping scaling factors for horizontal components of ground motions from subduction earthquakes using NGA-Subduction data","docAbstract":"

This article develops global models of damping scaling factors (DSFs) for subduction zone earthquakes that are functions of the damping ratio, spectral period, earthquake magnitude, and distance. The Next Generation Attenuation for subduction earthquakes (NGA-Sub) project has developed the largest uniformly processed database of recorded ground motions to date from seven subduction regions: Alaska, Cascadia, Central America and Mexico, South America, Japan, Taiwan, and New Zealand. NGA-Sub used this database to develop new ground motion models (GMMs) at a reference 5% damping ratio. We worked with the NGA-Sub project team to develop an extended database that includes pseudo-spectral accelerations (PSA) for 11 damping ratios between 0.5% and 30%. We use this database to develop parametric models of DSF for both interface and intraslab subduction earthquakes that can be used to adjust any subduction GMM from a reference 5% damping ratio to other damping ratios. The DSF is strongly influenced by the response spectral shape and the duration of motion; therefore, in addition to the damping ratio, the median DSF model uses spectral period, magnitude, and distance as surrogate predictor variables to capture the effects of the spectral shape and the duration of motion. We also develop parametric models for the standard deviation of DSF. The models presented in this article are for the RotD50 horizontal component of PSA and are compared with the models for shallow crustal earthquakes in active tectonic regions. Some noticeable differences arise from the considerably longer duration of interface records for very large magnitude events and the enriched high-frequency content of intraslab records, compared with shallow crustal earthquakes. Regional differences are discussed by comparing the proposed global models with the data from each subduction region along with recommendations on the applicability of the models.

","language":"English","publisher":"Sage","doi":"10.1177/87552930211027903","usgsCitation":"Rezaeian, S., Al Atik, L., Kuehn, N.M., Abrahamson, N., Bozorgnia, Y., Mazzoni, S., Withers, K., and Campbell, K., 2021, Spectral damping scaling factors for horizontal components of ground motions from subduction earthquakes using NGA-Subduction data: Earthquake Spectra, v. 37, no. 4, p. 2453-2492, https://doi.org/10.1177/87552930211027903.","productDescription":"40 p.","startPage":"2453","endPage":"2492","ipdsId":"IP-127852","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":393349,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"37","issue":"4","noUsgsAuthors":false,"publicationDate":"2021-07-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Rezaeian, Sanaz 0000-0001-7589-7893 srezaeian@usgs.gov","orcid":"https://orcid.org/0000-0001-7589-7893","contributorId":4395,"corporation":false,"usgs":true,"family":"Rezaeian","given":"Sanaz","email":"srezaeian@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":829051,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Al Atik, L.","contributorId":270335,"corporation":false,"usgs":false,"family":"Al Atik","given":"L.","affiliations":[{"id":56147,"text":"Linda Alatik Consulting, San Francisco, CA 94110","active":true,"usgs":false}],"preferred":false,"id":829052,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kuehn, N. M.","contributorId":270336,"corporation":false,"usgs":false,"family":"Kuehn","given":"N.","email":"","middleInitial":"M.","affiliations":[{"id":56148,"text":"University of California, Los Angeles, CA 90095","active":true,"usgs":false}],"preferred":false,"id":829053,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Abrahamson, N. A.","contributorId":27152,"corporation":false,"usgs":false,"family":"Abrahamson","given":"N. A.","affiliations":[],"preferred":false,"id":829054,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bozorgnia, Y.","contributorId":203475,"corporation":false,"usgs":false,"family":"Bozorgnia","given":"Y.","affiliations":[{"id":36629,"text":"University of California","active":true,"usgs":false}],"preferred":false,"id":829055,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Mazzoni, S.","contributorId":270337,"corporation":false,"usgs":false,"family":"Mazzoni","given":"S.","affiliations":[{"id":56148,"text":"University of California, Los Angeles, CA 90095","active":true,"usgs":false}],"preferred":false,"id":829056,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Withers, Kyle 0000-0001-7863-3930","orcid":"https://orcid.org/0000-0001-7863-3930","contributorId":203492,"corporation":false,"usgs":true,"family":"Withers","given":"Kyle","email":"","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":829057,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Campbell, K.","contributorId":63351,"corporation":false,"usgs":false,"family":"Campbell","given":"K.","affiliations":[{"id":47665,"text":"St. Anthony Falls Laboratory, University of Minnesota, Minneapolis, MN, USA","active":true,"usgs":false}],"preferred":false,"id":829058,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70222371,"text":"ofr20211067 - 2021 - U.S. Geological Survey science for the Wyoming Landscape Conservation Initiative—2018 annual report","interactions":[],"lastModifiedDate":"2021-07-27T11:55:40.554405","indexId":"ofr20211067","displayToPublicDate":"2021-07-26T18:00:00","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-1067","displayTitle":"U.S. Geological Survey Science for the Wyoming Landscape Conservation Initiative—2018 Annual Report","title":"U.S. Geological Survey science for the Wyoming Landscape Conservation Initiative—2018 annual report","docAbstract":"

The Wyoming Landscape Conservation Initiative (WLCI) was established in 2007 as a collaborative interagency partnership to develop and implement science-based conservation actions. During the past 11 years, partners from U.S. Geological Survey (USGS), State and Federal land management agencies, universities, and the public have collaborated to implement a long-term (more than 10 years) science-based program that assesses and enhances the quality and quantity of wildlife habitats in the southwest Wyoming region while facilitating responsible development. The USGS WLCI Science Team completes scientific research and develops tools that inform and support WLCI partner planning, decision making, and on-the-ground management actions.

In fiscal year 2018, the USGS initiated 3 new projects and continued efforts on 21 ongoing science and web-development projects. The first new project was initiated to support Secretarial Order 3362 which calls on the USGS to assist Western States in mapping big-game migration corridors and developing new mapping tools. During 2018, the USGS hosted a workshop in Laramie, Wyoming, which included more than 70 State and Federal wildlife experts from Colorado, New Mexico, Texas, and Wyoming. Most of the mapping and migration tool curricula used in the workshop were derived from prior WLCI studies and mapping efforts of big-game migration movement in habitats undergoing large-scale energy development.

The second new project was in response for WLCI partners to better understand sedimentation and hydrogeomorphic processes in a cold-desert headwater and the third new project was designed to improve our approach for people to access, manage, and analyze WLCI data and WLCI resource information. The USGS published 18 products (including peer-reviewed journal articles, USGS series publications, and data releases) and provided more than a dozen professional oral and poster presentations at scientific meetings and numerous informal presentations to WLCI partners at meetings and workshops. This report summarizes the objectives and status of each project and highlights the USGS 2018 accomplishments and products.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211067","usgsCitation":"Anderson, P.J., Aldridge, C.L., Alexander, J.S., Assal, T.J., Aulenbach, S., Bowen, Z.H., Chalfoun, A.D., Chong, G.W., Copeland, H., Edmunds, D.R., Germaine, S., Graves, T., Heinrichs, J.A., Homer, C.G., Huber, C.C., Johnston, A., Kauffman, M.J., Manier, D.J., McShan, R.R., Eddy-Miller, C.A., Miller, K.A., Monroe, A.P., O’Donnell, M.S., Ortega, A., Walters, A.W., Wieferich, D., Wyckoff, T.B., and Zeigenfuss, L., 2020, U.S. Geological Survey science for the Wyoming Landscape Conservation Initiative—2018 annual report: U.S. Geological Survey Open-File Report 2021–1067, 33 p., https://doi.org/10.3133/ofr20211067.","productDescription":"ix, 33 p.","onlineOnly":"Y","ipdsId":"IP-117398","costCenters":[{"id":207,"text":"Core Research Center","active":true,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":387403,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1067/coverthb.jpg"},{"id":387404,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1067/ofr20211067.pdf","text":"Report","size":"6.37 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021-1067"}],"country":"United States","state":"Wyoming","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.060791015625,\n 43.11702412135048\n ],\n [\n -111.060791015625,\n 41.02964338716638\n ],\n [\n -105.677490234375,\n 41.0130657870063\n ],\n [\n -105.875244140625,\n 41.60722821271717\n ],\n [\n -105.83129882812499,\n 42.32606244456202\n ],\n [\n -106.10595703125,\n 42.50450285299051\n ],\n [\n -107.083740234375,\n 42.49640294093705\n ],\n [\n -107.940673828125,\n 42.52879629320373\n ],\n [\n -108.896484375,\n 42.49640294093705\n ],\n [\n -109.3798828125,\n 42.62587560259137\n ],\n [\n -109.75341796875,\n 42.956422511073335\n ],\n [\n -110.06103515625,\n 43.197167282501276\n ],\n [\n -111.060791015625,\n 43.11702412135048\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director, Fort Collins Science Center
U.S. Geological Survey
2150 Centre Ave., Building C
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","tableOfContents":"","publishedDate":"2021-07-26","noUsgsAuthors":false,"publicationDate":"2021-07-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Anderson, Patrick J. 0000-0003-2281-389X andersonpj@usgs.gov","orcid":"https://orcid.org/0000-0003-2281-389X","contributorId":3590,"corporation":false,"usgs":true,"family":"Anderson","given":"Patrick","email":"andersonpj@usgs.gov","middleInitial":"J.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":819843,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Aldridge, Cameron L. 0000-0003-3926-6941 aldridgec@usgs.gov","orcid":"https://orcid.org/0000-0003-3926-6941","contributorId":191773,"corporation":false,"usgs":true,"family":"Aldridge","given":"Cameron","email":"aldridgec@usgs.gov","middleInitial":"L.","affiliations":[{"id":291,"text":"Fort Collins Science 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sensors","indexId":"ofr20211030","publicationYear":"2021","noYear":false,"title":"System characterization of Earth observation sensors"},"id":1}],"isPartOf":{"id":70221266,"text":"ofr20211030 - 2021 - System characterization of Earth observation sensors","indexId":"ofr20211030","publicationYear":"2021","noYear":false,"title":"System characterization of Earth observation sensors"},"lastModifiedDate":"2021-08-25T20:34:19.178126","indexId":"ofr20211030C","displayToPublicDate":"2021-07-26T16:11:28","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-1030","chapter":"C","displayTitle":"System Characterization Report on Planet’s Dove Classic","title":"System characterization report on Planet’s Dove Classic","docAbstract":"

Executive Summary

This report addresses system characterization of Planet’s Dove Classic satellites and is part of a series of system characterization reports produced and delivered by the U.S. Geological Survey Earth Resources Observation and Science Cal/Val Center of Excellence. These reports present and detail the methodology and procedures for characterization; present technical and operational information about the specific sensing system being evaluated; and provide a summary of test measurements, data retention practices, data analysis results, and conclusions.

Since 2013, Planet has launched more than 360 Dove 3U CubeSats, where U stands for 10-centimeter (cm) x 10-cm x 10-cm stowed dimensions, each weighing about 5 kilograms. Since 2015, all Dove satellites have had four-band imagers with about a 4-meter (m) pixel ground sample distance. Since 2016, all Doves have been launched into Sun-synchronous orbits varying from 474 to 524 kilometers, with inclinations between 97 and 98 degrees. The Dove series satellites do not have orbit maintenance capabilities; thus, their orbits decay slowly over time, contributing to shorter lifetimes of about 3 years. More information on Planet satellites and sensors is available in the “2020 Joint Agency Commercial Imagery Evaluation—Remote Sensing Satellite Compendium” and from the manufacturer at https://www.planet.com/.

The Earth Resources Observation and Science Cal/Val Center of Excellence system characterization team completed data analyses to characterize the geometric (interior and exterior), radiometric, and spatial performances. Results of these analyses indicate that Dove Classic has an interior geometric performance in the range of −0.218 (−0.073 pixel) to −0.037 m (−0.012 pixel) in easting and −0.167 (−0.056 pixel) to −0.111 m (−0.037 pixel) in northing in band-to-band registration, an exterior geometric error of −6.841 (−2.280 pixels) in easting and −6.235 m (−2.078 pixels) in northing offset in comparison to Landsat 8 Operational Land Imager, a radiometric performance in the range of −0.057 to −0.010 in offset and 0.963 to 1.298 in slope, and a spatial performance in the range of 2.77 to 3.35 pixels for full width at half maximum, with a modulation transfer function at a Nyquist frequency in the range of 0.003 to 0.010.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211030C","usgsCitation":"Kim, M., Park, S., Anderson, C., and Stensaas, G.L., 2021, System characterization report on Planet’s Dove Classic, chap. C of Ramaseri Chandra, S.N., comp., System characterization of Earth observation sensors: U.S. Geological Survey Open-File Report 2021–1030, 28 p., https://doi.org/10.3133/ofr20211030C.","productDescription":"v, 28 p.","numberOfPages":"38","onlineOnly":"Y","ipdsId":"IP-126677","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":387443,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1030/c/ofr20211030c.pdf","text":"Report","size":"31.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021–1030C"},{"id":387442,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1030/c/coverthb.jpg"}],"contact":"

Director, Earth Resources Observation and Science Center
U.S. Geological Survey
47914 252nd Street
Sioux Falls, SD 57198

Contact Pubs Warehouse

","tableOfContents":"","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2021-07-26","noUsgsAuthors":false,"publicationDate":"2021-07-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Kim, Minsu 0000-0003-4472-0926 minsukim@contractor.usgs.gov","orcid":"https://orcid.org/0000-0003-4472-0926","contributorId":216429,"corporation":false,"usgs":true,"family":"Kim","given":"Minsu","email":"minsukim@contractor.usgs.gov","affiliations":[{"id":54490,"text":"KBR, Inc., under contract to USGS","active":true,"usgs":false}],"preferred":true,"id":819907,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Park, Seonkyung 0000-0003-3203-1998","orcid":"https://orcid.org/0000-0003-3203-1998","contributorId":223182,"corporation":false,"usgs":true,"family":"Park","given":"Seonkyung","email":"","affiliations":[{"id":54490,"text":"KBR, Inc., under contract to USGS","active":true,"usgs":false}],"preferred":true,"id":819908,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Anderson, Cody 0000-0001-5612-1889 chanderson@usgs.gov","orcid":"https://orcid.org/0000-0001-5612-1889","contributorId":195521,"corporation":false,"usgs":true,"family":"Anderson","given":"Cody","email":"chanderson@usgs.gov","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":819909,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stensaas, Gregory L. 0000-0001-6679-2416 stensaas@usgs.gov","orcid":"https://orcid.org/0000-0001-6679-2416","contributorId":2551,"corporation":false,"usgs":true,"family":"Stensaas","given":"Gregory","email":"stensaas@usgs.gov","middleInitial":"L.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":819910,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70222384,"text":"ofr20211075 - 2021 - Evaluation of factors affecting migration success of adult sockeye salmon (Oncorhynchus nerka) in the Yakima River, Washington, 2020","interactions":[],"lastModifiedDate":"2021-07-27T11:39:13.986498","indexId":"ofr20211075","displayToPublicDate":"2021-07-26T10:54:53","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-1075","displayTitle":"Evaluation of Factors Affecting Migration Success of Adult Sockeye Salmon (Oncorhynchus nerka) in the Yakima River, Washington, 2020","title":"Evaluation of factors affecting migration success of adult sockeye salmon (Oncorhynchus nerka) in the Yakima River, Washington, 2020","docAbstract":"

A study was conducted during June–October 2020 to evaluate factors affecting the migration success of adult sockeye salmon (Oncorhynchus nerka) in the Yakima River, Washington. A total of 144 adult sockeye salmon were tagged and released during the study. Most fish (112 fish) were collected, tagged with passive integrated transponder (PIT), and released at the mouth of the Yakima River. The remaining fish were tagged with a radio transmitter and PIT tag: 13 fish were collected, tagged, and released at Prosser Dam; 13 fish were collected and tagged at Prosser Dam, transported downstream, and released at the mouth of the Yakima River; and 6 fish were collected, tagged, and released at the mouth of the Yakima River. Radio-tagged fish released at Prosser Dam initially moved upstream and spread out in the river reach between Prosser and Sunnyside Dams, but all fish stopped moving and several transmitters were recovered. Detection records and temperature data from recovered transmitters were the basis for inferring that avian predators consumed at least 6 of the 13 fish. Fifteen of the 19 radio-tagged sockeye salmon released at the mouth of the Yakima River moved upstream in the Columbia River and were detected at Johnson Island in the Hanford Reach, or at Priest Rapids Dam. Two of these fish, tagged on August 7, eventually moved back downstream and entered the Yakima River when water temperatures in the lower Yakima River were 16–18 degrees Celsius (°C). One fish moved upstream to Sunnyside Dam where its tag was later recovered. The other fish moved farther upstream and was detected at Prosser Dam, but eventually moved downstream and its tag was recovered near Benton City, Washington. None of the recovered tags were found near a carcass. More than one-half of the sockeye salmon that were collected, tagged, and released at the mouth of the Yakima River were subsequently detected, and the greatest proportion of fish from groups released during June, July, and August entered the Yakima River. This finding suggests that adult sockeye salmon are present at the mouth of the Yakima River throughout the summer. Detection records for tagged fish at monitoring sites located near cool water inputs in the lower Yakima River suggest that sockeye salmon do not spend a substantial amount of time at these locations. Fish count data at Prosser Dam fish ladders showed that sockeye salmon had a bi-modal pattern of upstream migration with peaks in late June/early July and September when water temperature in the lower Yakima River was 20 °C or less. Sixty-one percent of PIT-tagged sockeye salmon detected at Prosser Dam were eventually collected at the adult fish trapping facility at Roza Dam where fish are collected and transported upstream to Cle Elum Reservoir. These data, in conjunction with results from other studies, suggest that a substantial proportion of Yakima River sockeye salmon fail to arrive at Roza Dam. Additional research will be required to better understand factors affecting Yakima River sockeye salmon.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211075","collaboration":"Prepared in cooperation with Bureau of Reclamation, Yakama Nation Fisheries, and Washington Department of Fish and Wildlife","usgsCitation":"Kock, T.J., Hansen, A.C., Evans, S.D., Visser, R., Saluskin, B., Matala, A., and Hoffarth, P., 2021, Evaluation of factors affecting migration success of adult sockeye salmon (Oncorhynchus nerka) in the Yakima River, Washington, 2020: U.S. Geological Survey Open-File Report 2021–1075, 30 p., https://doi.org/10.3133/ofr20211075.","productDescription":"vi, 30 p.","onlineOnly":"Y","ipdsId":"IP-128700","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":387441,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1075/ofr20211075.pdf","text":"Report","size":"5.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021-1075"},{"id":387440,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1075/coverthb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Yakima River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.8770751953125,\n 45.96642454131025\n ],\n [\n -118.67431640625,\n 45.96642454131025\n ],\n [\n -118.67431640625,\n 46.916503267244835\n ],\n [\n -120.8770751953125,\n 46.916503267244835\n ],\n [\n -120.8770751953125,\n 45.96642454131025\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115-5016

","tableOfContents":"","publishedDate":"2021-07-26","noUsgsAuthors":false,"publicationDate":"2021-07-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Kock, Tobias J. 0000-0001-8976-0230 tkock@usgs.gov","orcid":"https://orcid.org/0000-0001-8976-0230","contributorId":3038,"corporation":false,"usgs":true,"family":"Kock","given":"Tobias","email":"tkock@usgs.gov","middleInitial":"J.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":819900,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hansen, Amy C. 0000-0002-0298-9137 achansen@usgs.gov","orcid":"https://orcid.org/0000-0002-0298-9137","contributorId":4350,"corporation":false,"usgs":true,"family":"Hansen","given":"Amy","email":"achansen@usgs.gov","middleInitial":"C.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":819901,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Evans, Scott D. 0000-0003-0452-7726 sdevans@usgs.gov","orcid":"https://orcid.org/0000-0003-0452-7726","contributorId":4408,"corporation":false,"usgs":true,"family":"Evans","given":"Scott","email":"sdevans@usgs.gov","middleInitial":"D.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":819902,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Visser, Richard","contributorId":223646,"corporation":false,"usgs":false,"family":"Visser","given":"Richard","email":"","affiliations":[{"id":7183,"text":"U.S. Bureau of Reclamation","active":true,"usgs":false}],"preferred":false,"id":819903,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Saluskin, Brian","contributorId":223647,"corporation":false,"usgs":false,"family":"Saluskin","given":"Brian","affiliations":[{"id":39287,"text":"Yakama Nation Fisheries","active":true,"usgs":false}],"preferred":false,"id":819904,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Matala, Andrew","contributorId":261352,"corporation":false,"usgs":false,"family":"Matala","given":"Andrew","affiliations":[],"preferred":false,"id":819905,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hoffarth, Paul","contributorId":177927,"corporation":false,"usgs":false,"family":"Hoffarth","given":"Paul","email":"","affiliations":[],"preferred":false,"id":819906,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70223494,"text":"70223494 - 2021 - Water–rock interaction and the concentrations of major, trace, and rare earth elements in hydrocarbon-associated produced waters of the United States","interactions":[],"lastModifiedDate":"2024-09-16T16:35:32.635392","indexId":"70223494","displayToPublicDate":"2021-07-26T07:46:46","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9161,"text":"Environmental Science: Processes & Impacts","active":true,"publicationSubtype":{"id":10}},"title":"Water–rock interaction and the concentrations of major, trace, and rare earth elements in hydrocarbon-associated produced waters of the United States","docAbstract":"

Studies of co-produced waters from hydrocarbon extraction across multiple energy-producing basins have generally focused on major ions or a few select tracers, and studies that examine trace elements and involve laboratory experiments have generally been basin specific. Here, new perspective is sought through a broad analysis of concentration data for 26 elements from three hydrocarbon well types using the U.S. Geological Survey National Produced Waters Geochemical Database (v2.3). Those data are compared to leachates (water, hydrochloric acid, and artificial brine) from 12 energy-resource related shales from across the United States. Both lower pH and higher ionic strength were associated with greater concentrations of many trace elements in produced waters. However, individual effects were difficult to distinguish because higher ionic strengths drive decreases in pH. Water–rock interactions in the leaching experiments generally replicated produced water concentrations for trace elements including Al, As, Cd, Co, Cu, Mo, Ni, Pb, Sb, Si, and Zn. Enhanced middle rare earth element (REE) mobilization relative to shale REE content occurred with low pH leachates. Produced water concentrations of Li, Sr, and Ba were not replicated by the leaching experiments. Patterns of high Li, Sr, and Ba concentrations and ratios relative to other elements across produced waters types indicate controls on these elements in many settings related to pore space pools of salts, brines, and ion-exchange sites affected by diagenetic processes. The size of those pools is diluted and masked by other water–rock interaction processes at the water–rock ratios necessitated by laboratory experiments. The results broadly link water–rock interaction processes and environmental patterns across a wide variety of produced waters and host formations and thus provide context for trace element data from other environmental and laboratory studies of such waters.

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Resources Program","active":true,"usgs":true}],"preferred":true,"id":822174,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jubb, Aaron M. 0000-0001-6875-1079","orcid":"https://orcid.org/0000-0001-6875-1079","contributorId":201978,"corporation":false,"usgs":true,"family":"Jubb","given":"Aaron M.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":822175,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70229346,"text":"70229346 - 2021 - Body size and digestive system shape resource selection by ungulates: A cross-taxa test of the forage maturation hypothesis","interactions":[],"lastModifiedDate":"2022-03-04T12:17:28.231597","indexId":"70229346","displayToPublicDate":"2021-07-26T05:58:22","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1466,"text":"Ecology Letters","active":true,"publicationSubtype":{"id":10}},"title":"Body size and digestive system shape resource selection by ungulates: A cross-taxa test of the forage maturation hypothesis","docAbstract":"

The forage maturation hypothesis (FMH) states that energy intake for ungulates is maximised when forage biomass is at intermediate levels. Nevertheless, metabolic allometry and different digestive systems suggest that resource selection should vary across ungulate species. By combining GPS relocations with remotely sensed data on forage characteristics and surface water, we quantified the effect of body size and digestive system in determining movements of 30 populations of hindgut fermenters (equids) and ruminants across biomes. Selection for intermediate forage biomass was negatively related to body size, regardless of digestive system. Selection for proximity to surface water was stronger for equids relative to ruminants, regardless of body size. To be more generalisable, we suggest that the FMH explicitly incorporate contingencies in body size and digestive system, with small-bodied ruminants selecting more strongly for potential energy intake, and hindgut fermenters selecting more strongly for surface water.

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We studied biotic ligand model (BLM) predictions of toxicity of nickel (Ni) and zinc (Zn) in natural waters from Illinois and Minnesota USA which had combinations of pH, hardness, and dissolved organic carbon (DOC) more extreme than 99.7% of waters in a nationwide database. We conducted 7-d chronic tests with Ceriodaphnia dubia, and 96-hr acute test and 14-d chronic tests with Neocloeon triangulifer, and estimated LC50s and EC20s for both species. Toxicity of Ni and Zn to both species differed among test waters by factors from 8 (Zn tests with C. dubia) to 35 (Zn tests with N. triangulifer). For both species and metals, tests with Minnesota waters (low pH and hardness, high DOC) showed lower toxicity than Illinois waters (high pH, high hardness, low DOC). Recalibration of the Ni BLM to be more responsive to pH-related changes improved predictions of Ni toxicity, especially for C. dubia. We compared several input data scenarios for the Zn BLM, which generally had minor effects on Model Performance Scores (MPS). A scenario that included inputs of modeled dissolved inorganic carbon and measured Al and Fe(III) produced highest MPS values for tests with both C. dubia and N. triangulifer. Overall, the BLM framework successfully modeled variation in toxicity for both Zn and Ni across wide ranges of water chemistry in tests with both standard and novel test organisms.

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County, New York","interactions":[],"lastModifiedDate":"2024-06-26T19:36:08.52945","indexId":"sir20215026","displayToPublicDate":"2021-07-23T10:10:00","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-5026","displayTitle":"Hydrogeology of the Susquehanna River Valley-Fill Aquifer System in the Towns of Conklin and Kirkwood, Broome County, New York","title":"Hydrogeology of the Susquehanna River valley-fill aquifer system in the towns of Conklin and Kirkwood, Broome County, New York","docAbstract":"

The hydrogeology of the Susquehanna River valley-fill aquifer system and adjacent areas in south-central Broome County, New York, was investigated in cooperation with the New York State Department of Environmental Conservation. The study area encompasses roughly 55.5 square miles and includes the towns of Conklin and Kirkwood. Multiple small, perhaps discontinuous, valley-fill aquifers of unknown extent and hydraulic interconnection underlie the Susquehanna River valley from easternmost Binghamton south to Riverside, New York, near the Pennsylvania border. The hydrogeologic framework of these aquifers is described in this report on the basis of existing descriptions of surficial materials, especially those related to deglaciation, and subsurface data extracted from well and boring logs. A compilation of surficial geology, the descriptions of the spatial distribution of confined and unconfined aquifers, hydrogeologic sections, and well locations is provided as an oversized map plate and in a U.S. Geological Survey data release.

Residential households are one of the principal consumers of groundwater in the study area. Approximately half of these households are served by public water-supply systems that obtain water from wells, chiefly from highly productive but small and likely discontinuous surficial deposits of sand and gravel, while others obtain water from sand-and-gravel aquifers beneath till and (or) fine-grained lacustrine deposits, and a few from bedrock. Residents outside the public-supply service areas rely on private wells. In till-mantled upland areas, nearly all private wells tap bedrock. Water-resource potential is likely greatest north of Kirkwood Center, New York, where the valley is narrowest, and local aquifers are in thick stratified glacial deposits. Well yields are highest in this part of the valley, and the local aquifer system is likely replenished through induced infiltration from the Susquehanna River and numerous small tributaries. The area between Langdon and Kirkwood is filled with a mixture of stratified and unstratified glacial sediments and contains one high-yield well. This area likely has moderate water-resource potential, but limited well data make this difficult to verify. Well yields from suitable stratified glacial sediments generally decrease southward toward Riverside, New York.

Characterizing potential groundwater resources is also helpful for prioritizing source-water-protection efforts. Water resources throughout New York are at risk of contamination from commercial and industrial surface activities. As in many valley areas throughout the Susquehanna River watershed in south-central New York, valley wells with depths greater than roughly 100 to 150 feet are susceptible to contamination by naturally occurring saltwater and methane. New York currently has a moratorium on hydraulic fracturing, but the study area is underlain by rocks suitable for unconventional methods of gas production that would likely be initiated if the moratorium were to be lifted.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215026","collaboration":"Prepared in cooperation with the New York State Department of Environmental Conservation","usgsCitation":"Van Hoesen, J.G., Heisig, P.M., and Fisher, S.R., 2021, Hydrogeology of the Susquehanna River valley-fill aquifer system in the towns of Conklin and Kirkwood, Broome County, New York: U.S. Geological Survey Scientific Investigations Report 2021–5026, 29 p., 1 pl., https://doi.org/10.3133/sir20215026.","productDescription":"Report: vii, 29 p.; 1 Plate 30.25 x 31.25 inches; Data Release","numberOfPages":"29","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-118763","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":387155,"rank":4,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2021/5026/sir20215026_plate1.pdf","text":"Plate 1","size":"1.82 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Detailed aquifer mapping of the Susquehanna River valley in south-central Broome County, towns of Conklin and Kirkwood, New York"},{"id":387154,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9O1EAV7","text":"USGS data release","linkHelpText":"Digital datasets for the hydrogeology of the Susquehanna River Valley in south-central Broome County, towns of Conklin and Kirkwood, New York"},{"id":387153,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5026/sir20215026.pdf","text":"Report","size":"8.25 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021-5026"},{"id":387152,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5026/coverthb2.jpg"}],"country":"United States","state":"New York","county":"Broome County","otherGeospatial":"Susquehanna River Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.91690063476561,\n 42.001345689029755\n ],\n [\n -75.74970245361328,\n 42.001345689029755\n ],\n [\n -75.74970245361328,\n 42.08803181932636\n ],\n [\n -75.91690063476561,\n 42.08803181932636\n ],\n [\n -75.91690063476561,\n 42.001345689029755\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director, New York Water Science Center
U.S. Geological Survey
425 Jordan Road
Troy, NY 12180–8349

","tableOfContents":"","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"publishedDate":"2021-07-23","noUsgsAuthors":false,"publicationDate":"2021-07-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Van Hoesen, John G. 0000-0003-2531-3794 jvanhoesen@usgs.gov","orcid":"https://orcid.org/0000-0003-2531-3794","contributorId":261007,"corporation":false,"usgs":true,"family":"Van Hoesen","given":"John","email":"jvanhoesen@usgs.gov","middleInitial":"G.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":819244,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Heisig, Paul M. 0000-0003-0338-4970 pmheisig@usgs.gov","orcid":"https://orcid.org/0000-0003-0338-4970","contributorId":793,"corporation":false,"usgs":true,"family":"Heisig","given":"Paul","email":"pmheisig@usgs.gov","middleInitial":"M.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":819243,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fisher, Shannon R. 0000-0001-8700-8504 srfisher@usgs.gov","orcid":"https://orcid.org/0000-0001-8700-8504","contributorId":261008,"corporation":false,"usgs":true,"family":"Fisher","given":"Shannon","email":"srfisher@usgs.gov","middleInitial":"R.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":819246,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70236265,"text":"70236265 - 2021 - Managing nonperennial headwater streams in temperate forests of the United States","interactions":[],"lastModifiedDate":"2022-08-31T14:27:51.450799","indexId":"70236265","displayToPublicDate":"2021-07-23T09:20:29","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1687,"text":"Forest Ecology and Management","active":true,"publicationSubtype":{"id":10}},"title":"Managing nonperennial headwater streams in temperate forests of the United States","docAbstract":"

Forest management guidelines are designed to protect water quality from unintended effects of land use changes such as timber harvest, mining, or forest road construction. Although streams that periodically cease to flow (nonperennial) drain the majority of forested areas, these streams are not consistently included in forest management guidelines. This paper reviews management guidelines for nonperennial (intermittent and ephemeral) streams draining temperate forests in the continental U.S., evaluates potential impacts of land use activities on ecosystem services provided by these streams, and identifies information needed to incorporate nonperennial streams into water quality protection practices. For federally administered lands, national management guidance is deliberately nonprescriptive, deferring to regional and forest-level recommendations for both perennial and nonperennial streams. Most state guidelines recommend riparian management zone (RMZ) protection for perennial streams (48/50 states) and intermittent streams (45/50 states), but only Alaska and West Virginia require RMZs around ephemeral streams. Based on the National Hydrography Dataset, an average of 58% of forested land area in the U.S. drains to nonperennial headwater streams, making these stream types the most common connectors between forested lands and the aquatic system. Land uses that modify flow regimes in these streams can affect sediment and organic matter transport and distribution, stream temperature dynamics, and biogeochemical processing. Nonperennial streams also provide material subsidies to downstream waters and serve as temporary habitats for some aquatic species. However, limited research has examined how forest land uses affect ecosystem services and biota in these streams. Therefore we highlight a set of key questions about nonperennial streams in forests, not the least of which is simply understanding where headwater stream channels are located and associated patterns of flow duration. Although many questions remain, we also note where recent advances in data collection, modeling and process-level research provide opportunities to resolve uncertainties around nonperennial streams in forested landscapes of the continental U.S.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.foreco.2021.119523","usgsCitation":"Kampf, S.K., Dwyer, K., Fairchild, M.P., Dunham, J.B., Snyder, C.D., Jaeger, K.L., Luce, C., Hammond, J., Wilson, C., Zimmer, M., and Sidell, M., 2021, Managing nonperennial headwater streams in temperate forests of the United States: Forest Ecology and Management, v. 497, 119523, 16 p., https://doi.org/10.1016/j.foreco.2021.119523.","productDescription":"119523, 16 p.","ipdsId":"IP-128255","costCenters":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"links":[{"id":405997,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"geometry\": {\n \"type\": \"MultiPolygon\",\n \"coordinates\": [\n [\n [\n [\n -94.81758,\n 49.38905\n ],\n [\n -94.64,\n 48.84\n 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Kathleen","contributorId":296016,"corporation":false,"usgs":false,"family":"Dwyer","given":"Kathleen","email":"","affiliations":[{"id":16848,"text":"USDA Forest Service, Rocky Mountain Research Station","active":true,"usgs":false}],"preferred":false,"id":850389,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fairchild, Matthew P.","contributorId":196533,"corporation":false,"usgs":false,"family":"Fairchild","given":"Matthew","email":"","middleInitial":"P.","affiliations":[{"id":24595,"text":"USDA Forest Service, Fort Collins CO","active":true,"usgs":false}],"preferred":false,"id":850390,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dunham, Jason B. 0000-0002-6268-0633 jdunham@usgs.gov","orcid":"https://orcid.org/0000-0002-6268-0633","contributorId":147808,"corporation":false,"usgs":true,"family":"Dunham","given":"Jason","email":"jdunham@usgs.gov","middleInitial":"B.","affiliations":[{"id":365,"text":"Leetown Science 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Center","active":true,"usgs":true}],"preferred":true,"id":850393,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Luce, Charles H.","contributorId":245593,"corporation":false,"usgs":false,"family":"Luce","given":"Charles H.","affiliations":[{"id":40027,"text":"United States Forest Service","active":true,"usgs":false}],"preferred":false,"id":850394,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hammond, John C. 0000-0002-4935-0736","orcid":"https://orcid.org/0000-0002-4935-0736","contributorId":223108,"corporation":false,"usgs":true,"family":"Hammond","given":"John C.","affiliations":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":850395,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Wilson, Codie","contributorId":296021,"corporation":false,"usgs":false,"family":"Wilson","given":"Codie","email":"","affiliations":[{"id":63967,"text":"Natural Resource Ecology Lab, Colorado State University","active":true,"usgs":false}],"preferred":false,"id":850396,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Zimmer, Margaret","contributorId":296022,"corporation":false,"usgs":false,"family":"Zimmer","given":"Margaret","affiliations":[{"id":27155,"text":"University of California Santa Cruz","active":true,"usgs":false}],"preferred":false,"id":850397,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Sidell, Marielle","contributorId":296023,"corporation":false,"usgs":false,"family":"Sidell","given":"Marielle","email":"","affiliations":[{"id":63968,"text":"Department of Ecosystem Science and Sustainability, Colorado State University","active":true,"usgs":false}],"preferred":false,"id":850398,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70249293,"text":"70249293 - 2021 - The products of primary magma fragmentation finally revealed by pumice agglomerates","interactions":[],"lastModifiedDate":"2023-10-03T12:11:05.896246","indexId":"70249293","displayToPublicDate":"2021-07-23T07:07:31","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1796,"text":"Geology","active":true,"publicationSubtype":{"id":10}},"title":"The products of primary magma fragmentation finally revealed by pumice agglomerates","docAbstract":"

Following rapid decompression in the conduit of a volcano, magma breaks into ash- to block-sized fragments, powering explosive sub-Plinian and Plinian eruptions that may generate destructive pyroclastic falls and flows. It is thus crucial to assess how magma breaks up into fragments. This task is difficult, however, because of the subterranean nature of the entire process and because the original size of pristine fragments is modified by secondary fragmentation and expansion. New textural observations of sub-Plinian and Plinian pumice lapilli reveal that some primary products of magma fragmentation survive by sintering together within seconds of magma break-up. Their size distributions reflect the energetics of fragmentation, consistent with products of rapid decompression experiments. Pumice aggregates thus offer a unique window into the previously inaccessible primary fragmentation process and could be used to determine the potential energy of fragmentation.

","language":"English","publisher":"Geological Society of America","doi":"10.1130/G48902.1","usgsCitation":"Giachetti, T., Trafton, K., Wiejaczka, J., Gardner, J., Watkins, J.M., Shea, T., and Wright, H.M., 2021, The products of primary magma fragmentation finally revealed by pumice agglomerates: Geology, v. 49, no. 11, p. 1307-1311, https://doi.org/10.1130/G48902.1.","productDescription":"5 p.","startPage":"1307","endPage":"1311","ipdsId":"IP-129407","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":451431,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/g48902.1","text":"Publisher Index Page"},{"id":421530,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"49","issue":"11","noUsgsAuthors":false,"publicationDate":"2021-07-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Giachetti, Thomas 0000-0003-1360-6768","orcid":"https://orcid.org/0000-0003-1360-6768","contributorId":287591,"corporation":false,"usgs":false,"family":"Giachetti","given":"Thomas","email":"","affiliations":[{"id":6604,"text":"University of Oregon","active":true,"usgs":false}],"preferred":false,"id":885021,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Trafton, Kathy 0000-0002-7688-4397","orcid":"https://orcid.org/0000-0002-7688-4397","contributorId":330475,"corporation":false,"usgs":false,"family":"Trafton","given":"Kathy","email":"","affiliations":[{"id":6604,"text":"University of Oregon","active":true,"usgs":false}],"preferred":false,"id":885022,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wiejaczka, Joshua 0000-0002-9573-3279","orcid":"https://orcid.org/0000-0002-9573-3279","contributorId":330476,"corporation":false,"usgs":false,"family":"Wiejaczka","given":"Joshua","email":"","affiliations":[{"id":6604,"text":"University of Oregon","active":true,"usgs":false}],"preferred":false,"id":885023,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gardner, James E.","contributorId":292118,"corporation":false,"usgs":false,"family":"Gardner","given":"James E.","affiliations":[{"id":12430,"text":"University of Texas at Austin","active":true,"usgs":false}],"preferred":false,"id":885024,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Watkins, James M.","contributorId":189286,"corporation":false,"usgs":false,"family":"Watkins","given":"James","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":885025,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Shea, Tom 0000-0001-7378-684X","orcid":"https://orcid.org/0000-0001-7378-684X","contributorId":223773,"corporation":false,"usgs":false,"family":"Shea","given":"Tom","email":"","affiliations":[{"id":39036,"text":"University of Hawaii at Manoa","active":true,"usgs":false}],"preferred":false,"id":885026,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wright, Heather M. 0000-0001-9013-507X hwright@usgs.gov","orcid":"https://orcid.org/0000-0001-9013-507X","contributorId":3949,"corporation":false,"usgs":true,"family":"Wright","given":"Heather","email":"hwright@usgs.gov","middleInitial":"M.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":885027,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70222446,"text":"70222446 - 2021 - Response to Gard et al.'s (2021) Comments on the Critical Review “Polychlorinated Biphenyl Tissue-Concentration Thresholds for Survival, Growth, and Reproduction in Fish”","interactions":[],"lastModifiedDate":"2021-07-30T14:07:48.417788","indexId":"70222446","displayToPublicDate":"2021-07-22T09:07:04","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1571,"text":"Environmental Toxicology and Chemistry","active":true,"publicationSubtype":{"id":10}},"title":"Response to Gard et al.'s (2021) Comments on the Critical Review “Polychlorinated Biphenyl Tissue-Concentration Thresholds for Survival, Growth, and Reproduction in Fish”","docAbstract":"

This response is offered to the critique by Gard et al. (2021) of our meta-analysis of polychlorinated biphenyl (PCB)-induced toxicity data in fish (Berninger and Tillitt 2019). Gard et al. (2021) offered numerous comments, the most substantive suggesting that 1) we should have added no-observable–adverse effect residue (NOAER) data from additional studies and all data points from selected studies, and 2) the uncertainty of aggregating data from different PCB mixtures, different species, and different life stages is too great based on a limited data set. The additional studies Gard et al. suggested either were not designed to produce toxicological data, had experimental design issues, were confounded by co-contaminants, or did not contain paired exposure–effects data and as such were not appropriate to add to the data set. Lowest-observable–adverse effect residue (LOAER) values were selected for our analysis because they represent population sensitivities from the central portions of a frequency distribution (the linear portion of dose–response curves). As a consequence, there is less uncertainty in these input data (LOAER values) and greater confidence that they accurately represent the response of fish populations tested. Modeling NOAER values is in the extrapolation portion of a dose–response relationship and subject to enhanced uncertainty. The Gard et al. (2021) critique ignores this fundamental principle of toxicology and adds/deletes data points from our data set without clear selection criteria, which artificially enhances the uncertainty of their models that ultimately are not useful. We reject the premise that it is better to use individual study data as opposed to aggregation of PCB-induced toxicity thresholds in fish.

","language":"English","publisher":"Society for Environmental Toxicology and Chemistry (SETAC)","doi":"10.1002/etc.5074","usgsCitation":"Berninger, J., and Tillitt, D.E., 2021, Response to Gard et al.'s (2021) Comments on the Critical Review “Polychlorinated Biphenyl Tissue-Concentration Thresholds for Survival, Growth, and Reproduction in Fish”: Environmental Toxicology and Chemistry, v. 8, no. 40, p. 2098-2109, https://doi.org/10.1002/etc.5074.","productDescription":"12 p.","startPage":"2098","endPage":"2109","ipdsId":"IP-127386","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":498904,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/etc.5074","text":"Publisher Index Page"},{"id":387596,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","issue":"40","noUsgsAuthors":false,"publicationDate":"2021-08-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Berninger, Jason P.","contributorId":173602,"corporation":false,"usgs":false,"family":"Berninger","given":"Jason P.","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":820064,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tillitt, Donald E. 0000-0002-8278-3955 dtillitt@usgs.gov","orcid":"https://orcid.org/0000-0002-8278-3955","contributorId":1875,"corporation":false,"usgs":true,"family":"Tillitt","given":"Donald","email":"dtillitt@usgs.gov","middleInitial":"E.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":820065,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70255193,"text":"70255193 - 2021 - Habitat selection by wolves and mountain lions during summer in western Montana","interactions":[],"lastModifiedDate":"2024-06-17T12:16:31.493985","indexId":"70255193","displayToPublicDate":"2021-07-22T07:13:58","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Habitat selection by wolves and mountain lions during summer in western Montana","docAbstract":"

In the Northern Rockies of the United States, predators like wolves (Canis lupus) and mountain lions (Puma concolor) have been implicated in fluctuations or declines in populations of game species like elk (Cervus canadensis) and mule deer (Odocoileus hemionus). In particular, local distributions of these predators may affect ungulate behavior, use of space, and dynamics. Our goal was to develop generalizable predictions of habitat selection by wolves and mountain lions across western Montana. We hypothesized both predator species would select habitat that maximized their chances of encountering and killing ungulates and that minimized their chances of encountering humans. We assessed habitat selection by these predators during summer using within-home range (3rd order) resource selection functions (RSFs) in multiple study areas throughout western Montana, and tested how generalizable RSF predictions were by applying them to out-of-sample telemetry data from separate study areas. Selection for vegetation cover-types varied substantially among wolves in different study areas. Nonetheless, our predictions of 3rd order selection by wolves were highly generalizable across different study areas. Wolves consistently selected simple topography where ungulate prey may be more susceptible to their cursorial hunting mode. Topographic features may serve as better proxies of predation risk by wolves than vegetation cover-types. Predictions of mountain lion distribution were less generalizable. Use of rugged terrain by mountain lions varied across ecosystem-types, likely because mountain lions targeted the habitats of different prey species in each study area. Our findings suggest that features that facilitate the hunting mode of a predator (i.e. simple topography for cursorial predators and hiding cover for stalking predators) may be more generalizable predictors of their habitat selection than features associated with local prey densities.

","language":"English","publisher":"PLoS","doi":"10.1371/journal.pone.0254827","usgsCitation":"Mitchell, M.S., Peterson, C.J., DeCesare, N., Bishop, C.J., and Sells, S.S., 2021, Habitat selection by wolves and mountain lions during summer in western Montana: PLoS ONE, v. 16, no. 7, e0254827, 24 p., https://doi.org/10.1371/journal.pone.0254827.","productDescription":"e0254827, 24 p.","ipdsId":"IP-130414","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":451439,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0254827","text":"Publisher Index Page"},{"id":430267,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -116.20539211607286,\n 49.10228144307132\n ],\n [\n -116.20539211607286,\n 46.39960463532046\n ],\n [\n -111.34943508482237,\n 46.39960463532046\n ],\n [\n -111.34943508482237,\n 49.10228144307132\n ],\n [\n -116.20539211607286,\n 49.10228144307132\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"16","issue":"7","noUsgsAuthors":false,"publicationDate":"2021-07-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Mitchell, Michael S. 0000-0002-0773-6905 mmitchel@usgs.gov","orcid":"https://orcid.org/0000-0002-0773-6905","contributorId":3716,"corporation":false,"usgs":true,"family":"Mitchell","given":"Michael","email":"mmitchel@usgs.gov","middleInitial":"S.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":903703,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Peterson, Collin J.","contributorId":338960,"corporation":false,"usgs":false,"family":"Peterson","given":"Collin","email":"","middleInitial":"J.","affiliations":[{"id":48645,"text":"umt","active":true,"usgs":false}],"preferred":false,"id":903704,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"DeCesare, Nicholas J.","contributorId":338961,"corporation":false,"usgs":false,"family":"DeCesare","given":"Nicholas J.","affiliations":[{"id":48627,"text":"mtfwp","active":true,"usgs":false}],"preferred":false,"id":903705,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bishop, Chad J.","contributorId":338963,"corporation":false,"usgs":false,"family":"Bishop","given":"Chad","email":"","middleInitial":"J.","affiliations":[{"id":48645,"text":"umt","active":true,"usgs":false}],"preferred":false,"id":903706,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sells, Sarah S.","contributorId":338966,"corporation":false,"usgs":false,"family":"Sells","given":"Sarah","email":"","middleInitial":"S.","affiliations":[{"id":48645,"text":"umt","active":true,"usgs":false}],"preferred":false,"id":903707,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70222417,"text":"70222417 - 2021 - Evaluation of a two-season banding program to estimate and model migratory bird survival","interactions":[],"lastModifiedDate":"2021-10-06T15:36:39.723512","indexId":"70222417","displayToPublicDate":"2021-07-22T07:11:54","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":"Evaluation of a two-season banding program to estimate and model migratory bird survival","docAbstract":"

The management of North American waterfowl is predicated on long-term, continental scale banding implemented prior to the hunting season (i.e., July–September) and subsequent reporting of bands recovered by hunters. However, single-season banding and encounter operations have a number of characteristics that limit their application to estimating demographic rates and evaluating hypothesized limiting factors throughout the annual cycle. We designed and implemented a 2-season banding program for American black ducks (Anas rubripes), mallards (A. platyrhynchos), and hybrids in eastern North America to evaluate potential application to annual life cycle conservation and sport harvest management. We assessed model fit and compared estimates of annual survival among data types (i.e., pre-hunting season only [July–September], post-hunting season only [January–March], and 2-season [pre- and post-hunting season]) to evaluate model assumptions and potential application to population modeling and management. There was generally high agreement between estimates of annual survival derived using 2-season and pre-season only data for all age and sex cohorts. Estimates of annual survival derived from post-season banding data only were consistently higher for adult females and juveniles of both sexes. We found patterns of seasonal survival varied by species, age, and to a lesser extent, sex. Hunter recovered birds exhibited similar spatial distributions regardless of banding season suggesting banded samples were from the same population. In contrast, Goodness-Of-Fit tests suggest this assumption was statistically violated in some regions and years. We conclude that estimates of seasonal and annual survival for black ducks and mallards based on the 2-season banding program are valid and accurate based on model fit statistics, similarity in survival estimates across data and models, and similarities in the distribution of recoveries. The 2-season program provides greater precision and insight into the survival process and will improve the ability of researchers and managers to test competing hypotheses regarding population regulation resulting in more effective management.

","language":"English","publisher":"Ecological Society of America","doi":"10.1002/eap.2425","usgsCitation":"Devers, P.K., Emmet, R., Boomer, G.S., Zimmerman, G.S., and Royle, J., 2021, Evaluation of a two-season banding program to estimate and model migratory bird survival: Ecological Applications, v. 31, no. 7, e02425, 18 p., https://doi.org/10.1002/eap.2425.","productDescription":"e02425, 18 p.","ipdsId":"IP-127019","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":387503,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"31","issue":"7","noUsgsAuthors":false,"publicationDate":"2021-08-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Devers, Patrick K.","contributorId":261406,"corporation":false,"usgs":false,"family":"Devers","given":"Patrick","email":"","middleInitial":"K.","affiliations":[{"id":7199,"text":"US FWS","active":true,"usgs":false}],"preferred":false,"id":819981,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Emmet, Robert L.","contributorId":261407,"corporation":false,"usgs":false,"family":"Emmet","given":"Robert L.","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":819982,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Boomer, G. Scott 0000-0001-5854-3604","orcid":"https://orcid.org/0000-0001-5854-3604","contributorId":261408,"corporation":false,"usgs":false,"family":"Boomer","given":"G.","email":"","middleInitial":"Scott","affiliations":[{"id":7199,"text":"US FWS","active":true,"usgs":false}],"preferred":true,"id":819983,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zimmerman, Guthrie S.","contributorId":261410,"corporation":false,"usgs":false,"family":"Zimmerman","given":"Guthrie","email":"","middleInitial":"S.","affiliations":[{"id":7199,"text":"US FWS","active":true,"usgs":false}],"preferred":false,"id":819984,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Royle, J. Andrew 0000-0003-3135-2167 aroyle@usgs.gov","orcid":"https://orcid.org/0000-0003-3135-2167","contributorId":3504,"corporation":false,"usgs":true,"family":"Royle","given":"J. Andrew","email":"aroyle@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":819985,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70226499,"text":"70226499 - 2021 - Is the grass always greener? Land surface phenology reveals differences in peak and season-long vegetation productivity responses to climate and management","interactions":[],"lastModifiedDate":"2021-11-22T13:10:05.542882","indexId":"70226499","displayToPublicDate":"2021-07-22T07:04:09","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Is the grass always greener? Land surface phenology reveals differences in peak and season-long vegetation productivity responses to climate and management","docAbstract":"

Vegetation phenology—the seasonal timing and duration of vegetative phases—is controlled by spatiotemporally variable contributions of climatic and environmental factors plus additional potential influence from human management. We used land surface phenology derived from the Advanced Very High Resolution Radiometer and climate data to examine variability in vegetation productivity and phenological dates from 1989 to 2014 in the U.S. Northwestern Plains, a region with notable spatial heterogeneity in climate, vegetation, and land use. We first analyzed interannual trends in six phenological measures as a baseline. We then demonstrated how including annual-resolution predictors can provide more nuanced insights into measures of phenology between plant communities and across the ecoregion. Across the study area, higher annual precipitation increased both peak and season-long productivity. In contrast, higher mean annual temperatures tended to increase peak productivity but for the majority of the study area decreased season-long productivity. Annual precipitation and temperature had strong explanatory power for productivity-related phenology measures but predicted date-based measures poorly. We found that relationships between climate and phenology varied across the region and among plant communities and that factors such as recovery from disturbance and anthropogenic management also contributed in certain regions. In sum, phenological measures did not respond ubiquitously nor covary in their responses. Nonclimatic dynamics can decouple phenology from climate; therefore, analyses including only interannual trends should not assume climate alone drives patterns. For example, models of areas exhibiting greening or browning should account for climate, anthropogenic influence, and natural disturbances. Investigating multiple aspects of phenology to describe growing-season dynamics provides a richer understanding of spatiotemporal patterns that can be used for predicting ecosystem responses to future climates and land-use change. Such understanding allows for clearer interpretation of results for conservation, wildlife, and land management.

","language":"English","publisher":"Wiley","doi":"10.1002/ece3.7904","usgsCitation":"Wood, D.J., Powell, S., Stoy, P.C., Thurman, L., and Beever, E.A., 2021, Is the grass always greener? Land surface phenology reveals differences in peak and season-long vegetation productivity responses to climate and management: Ecology and Evolution, v. 11, no. 16, p. 11168-11199, https://doi.org/10.1002/ece3.7904.","productDescription":"32 p.","startPage":"11168","endPage":"11199","ipdsId":"IP-123458","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":451442,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1002/ece3.7904","text":"External Repository"},{"id":391973,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11","issue":"16","noUsgsAuthors":false,"publicationDate":"2021-07-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Wood, David J. A. 0000-0003-4315-5160 dwood@usgs.gov","orcid":"https://orcid.org/0000-0003-4315-5160","contributorId":177588,"corporation":false,"usgs":true,"family":"Wood","given":"David","email":"dwood@usgs.gov","middleInitial":"J. A.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":827115,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Powell, Scott","contributorId":192347,"corporation":false,"usgs":false,"family":"Powell","given":"Scott","affiliations":[],"preferred":false,"id":827116,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stoy, Paul C.","contributorId":204157,"corporation":false,"usgs":false,"family":"Stoy","given":"Paul","email":"","middleInitial":"C.","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":827117,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thurman, Lindsey 0000-0003-3142-4909","orcid":"https://orcid.org/0000-0003-3142-4909","contributorId":269425,"corporation":false,"usgs":true,"family":"Thurman","given":"Lindsey","email":"","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":827118,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Beever, Erik A. 0000-0002-9369-486X ebeever@usgs.gov","orcid":"https://orcid.org/0000-0002-9369-486X","contributorId":2934,"corporation":false,"usgs":true,"family":"Beever","given":"Erik","email":"ebeever@usgs.gov","middleInitial":"A.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":827119,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70222095,"text":"fs20203064 - 2021 - Water resources of Grant Parish, Louisiana","interactions":[],"lastModifiedDate":"2021-07-21T11:36:55.289869","indexId":"fs20203064","displayToPublicDate":"2021-07-20T14:29:55","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2020-3064","displayTitle":"Water Resources of Grant Parish, Louisiana","title":"Water resources of Grant Parish, Louisiana","docAbstract":"

Information concerning the availability, use, and quality of water in Grant Parish, Louisiana, is critical for proper water-supply management. The purpose of this fact sheet is to present information that can be used by water managers, parish residents, and others for stewardship of this vital resource. In 2014, about 5.43 million gallons per day (Mgal/d) of water were withdrawn in Grant Parish, including about 2.39 Mgal/d from groundwater sources and 3.03 Mgal/d from surface-water sources. Withdrawals for public-supply use accounted for 71 percent (3.84 Mgal/d) of the total water withdrawn. Withdrawals for agricultural use, composed of general irrigation and livestock uses, accounted for 24 percent (1.28 Mgal/d) of the total water withdrawn. Other categories of use included industrial and rural domestic. Water-use data collected at 5-year intervals from 1960 to 2010 and again in 2014 indicated that water withdrawals peaked in 1960.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20203064","collaboration":"Prepared in cooperation with the Louisiana Department of Transportation and Development","usgsCitation":"Murphy, C.J., and White, V.E., 2021, Water resources of Grant Parish, Louisiana: U.S. Geological Survey Fact Sheet 2020–3064, 6 p., https://doi.org/10.3133/fs20203064.","productDescription":"Report: 6 p.; Data Release","numberOfPages":"6","onlineOnly":"N","ipdsId":"IP-103348","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":387262,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2020/3064/coverthb.jpg"},{"id":387263,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2020/3064/fs20203064.pdf","text":"Report","size":"1.04 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 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Director, Lower Mississippi-Gulf Water Science Center
U.S. Geological Survey
3535 S. Sherwood Forest Blvd., Suite 120
Baton Rouge, LA 70816

","tableOfContents":"","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"publishedDate":"2021-07-20","noUsgsAuthors":false,"publicationDate":"2021-07-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Murphy, Chid J. 0000-0001-9675-8382","orcid":"https://orcid.org/0000-0001-9675-8382","contributorId":223073,"corporation":false,"usgs":false,"family":"Murphy","given":"Chid","email":"","middleInitial":"J.","affiliations":[{"id":40665,"text":"U.S. Bureau of Indian Affairs","active":true,"usgs":false}],"preferred":false,"id":819491,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"White, Vincent E. 0000-0002-1660-0102 vwhite@usgs.gov","orcid":"https://orcid.org/0000-0002-1660-0102","contributorId":5388,"corporation":false,"usgs":true,"family":"White","given":"Vincent","email":"vwhite@usgs.gov","middleInitial":"E.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":819492,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70222354,"text":"70222354 - 2021 - Response of forage plants to alteration of temperature and spring thaw date: Implications for geese in a warming Arctic","interactions":[],"lastModifiedDate":"2021-07-22T13:54:40.090154","indexId":"70222354","displayToPublicDate":"2021-07-20T08:48:03","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Response of forage plants to alteration of temperature and spring thaw date: Implications for geese in a warming Arctic","docAbstract":"

Changes in summer temperatures in Arctic Alaska have led to longer and warmer growing seasons over the last three decades. Corresponding with these changes in climate, the abundance and distributions of geese have increased and expanded over the same period. We used an experimental approach to assess the response of goose forage plants to simulated environmental change. We subjected Carex subspathacea, a preferred goose forage growing on the Arctic Coastal Plain (ACP) of Alaska, to manipulations of temperature and timing of spring thaw to measure potential effects in terms of plant nitrogen concentration, aboveground biomass, and total nitrogen availability. Carex subspathacea responded to warming in a dynamic fashion. Increases in temperature led to decreases in leaf nitrogen concentration but increases in aboveground biomass. The increase in biomass was stronger than the decline in nitrogen concentration such that total nitrogen availability was increased with temperature for the first 35–40 d of the season. Grazing removal accounted for only minimal offtake of biomass, and we found no indication that grazing maintained elevated levels of nitrogen concentration longer in the season as reported in other studies. Based on demonstrated relationships in the literature between forage nitrogen concentrations and gosling growth rates, we conclude that there is currently abundant high-quality forage available across the ACP. This finding fits with recent evidence of high gosling growth rates and increasing trends in goose abundance on the ACP. Our results suggest that with climate warming of a few degrees, nitrogen concentration of forage may decrease, but forage biomass and total nitrogen availability will increase. Our data suggest that nitrogen concentration will not fall below the minimum threshold required by geese in the near future. As such, we suggest that there is currently no bottom-up limitation to goose numbers on the ACP.

","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.3627","usgsCitation":"Flint, P.L., and Meixell, B.W., 2021, Response of forage plants to alteration of temperature and spring thaw date: Implications for geese in a warming Arctic: Ecosphere, v. 12, no. 7, e03627, 17 p., https://doi.org/10.1002/ecs2.3627.","productDescription":"e03627, 17 p.","ipdsId":"IP-121569","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":489092,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.3627","text":"Publisher Index Page"},{"id":436268,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9WMFBVN","text":"USGS data release","linkHelpText":"Vegetation and Temperature Data, Smith River Estuary, Alaska, 2011-2013"},{"id":387378,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Smith River Estuary","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -153.358154296875,\n 70.84929093589197\n ],\n [\n -153.0965423583984,\n 70.84929093589197\n ],\n [\n -153.0965423583984,\n 70.92281373736292\n ],\n [\n -153.358154296875,\n 70.92281373736292\n ],\n [\n -153.358154296875,\n 70.84929093589197\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"12","issue":"7","noUsgsAuthors":false,"publicationDate":"2021-07-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Flint, Paul L. 0000-0002-8758-6993 pflint@usgs.gov","orcid":"https://orcid.org/0000-0002-8758-6993","contributorId":3284,"corporation":false,"usgs":true,"family":"Flint","given":"Paul","email":"pflint@usgs.gov","middleInitial":"L.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":819732,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Meixell, Brandt W. 0000-0002-6738-0349 bmeixell@usgs.gov","orcid":"https://orcid.org/0000-0002-6738-0349","contributorId":138716,"corporation":false,"usgs":true,"family":"Meixell","given":"Brandt","email":"bmeixell@usgs.gov","middleInitial":"W.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":819733,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ]}