We present measurements of the density, hydraulic conductivity, and specific discharge of a widespread firn aquifer in Antarctica, within the Wilkins Ice Shelf. At the field site, the aquifer is 16.2 m thick, starting at 13.4 m from the snow surface and transitioning from water‐saturated firn to ice at 29.6 m. Hydraulic conductivity derived from slug tests show a geometric mean value of 1.4 ± 1.2 × 10−4 m s−1, equivalent to permeability of 2.6 ± 2.2 × 10−11 m2. A borehole dilution test indicates an average specific discharge value of 1.9 ± 2.8 × 10−6 m s−1. Ground‐penetrating radar profiles and a groundwater flow model show the aquifer is draining laterally into a large nearby rift. Our findings indicate that the firn aquifer in the vicinity of the field site is likely not in a steady state and its presence likely contributed to past ice shelf instability.
","language":"English","publisher":"Wiley","doi":"10.1029/2020GL089552","usgsCitation":"Montgomery, L., Miege, C., MIller, J., Wallin, B., Miller, O.L., Scambos, T.A., Solomon, D., Forster, R., and Koenig, L., 2020, Hydrologic properties of a highly permeable firn aquifer in the Wilkins Ice Shelf, Antarctica: Geophysical Research Letters, v. 47, e2020GL089552, 10 p., https://doi.org/10.1029/2020GL089552.","productDescription":"e2020GL089552, 10 p.","ipdsId":"IP-119455","costCenters":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"links":[{"id":454923,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1029/2020gl089552","text":"External Repository"},{"id":382525,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Antarctica, Wilkins Ice Sheet","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -71.54022216796875,\n -71.79883675782347\n ],\n [\n -70.400390625,\n -71.79883675782347\n ],\n [\n -70.400390625,\n -71.54143894204527\n ],\n [\n -71.54022216796875,\n -71.54143894204527\n ],\n [\n -71.54022216796875,\n -71.79883675782347\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"47","noUsgsAuthors":false,"publicationDate":"2020-11-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Montgomery, Lynn","contributorId":244036,"corporation":false,"usgs":false,"family":"Montgomery","given":"Lynn","email":"","affiliations":[{"id":36627,"text":"University of Colorado, Boulder","active":true,"usgs":false}],"preferred":false,"id":803105,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Miege, C.","contributorId":248303,"corporation":false,"usgs":false,"family":"Miege","given":"C.","email":"","affiliations":[],"preferred":false,"id":808855,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"MIller, Julie","contributorId":248311,"corporation":false,"usgs":false,"family":"MIller","given":"Julie","email":"","affiliations":[],"preferred":false,"id":808856,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wallin, Bruce","contributorId":248312,"corporation":false,"usgs":false,"family":"Wallin","given":"Bruce","email":"","affiliations":[],"preferred":false,"id":808857,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Scambos, Ted A.","contributorId":57367,"corporation":false,"usgs":true,"family":"Scambos","given":"Ted","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":808858,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Miller, Olivia L. 0000-0002-8846-7048","orcid":"https://orcid.org/0000-0002-8846-7048","contributorId":216556,"corporation":false,"usgs":true,"family":"Miller","given":"Olivia","email":"","middleInitial":"L.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":803106,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Solomon, D Kip","contributorId":146290,"corporation":false,"usgs":false,"family":"Solomon","given":"D Kip","affiliations":[{"id":7215,"text":"University of Utah Dept. of Geography","active":true,"usgs":false}],"preferred":false,"id":808859,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Forster, Richard","contributorId":172149,"corporation":false,"usgs":false,"family":"Forster","given":"Richard","affiliations":[{"id":26993,"text":"University of Utah, Department of Geography","active":true,"usgs":false}],"preferred":false,"id":808860,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Koenig, Lora","contributorId":248313,"corporation":false,"usgs":false,"family":"Koenig","given":"Lora","affiliations":[],"preferred":false,"id":808861,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70215786,"text":"ds1131 - 2020 - Fish assemblages in eelgrass beds of Bellingham Bay, Washington, Northern Puget Sound, 2019","interactions":[],"lastModifiedDate":"2020-10-30T15:31:44.761418","indexId":"ds1131","displayToPublicDate":"2020-10-29T11:53:31","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"1131","displayTitle":"Fish Assemblages in Eelgrass Beds of Bellingham Bay, Washington, Northern Puget Sound, 2019","title":"Fish assemblages in eelgrass beds of Bellingham Bay, Washington, Northern Puget Sound, 2019","docAbstract":"Puget Sound is a critical part of the Pacific Northwest, both culturally and economically. Eelgrass beds are an important feature of Puget Sound and are known to influence fish assemblages. As part of a larger site-characterization effort, and to gain a better understanding of the fish assemblages in Bellingham Bay, Washington, four eelgrass beds (Zostera marina) along the shoreline were surveyed. Fish were captured from 24 through 26 September 2019 by using three beach-seine hauls per eelgrass bed. In total, 12 hauls yielded 2,135 fish that comprised 20 species from 14 families. Shiner perch (Cymatogaster aggregata) accounted for 52 percent of the total catch. The other common species included three-spine stickleback (Gasterosteus aculeatus), bay pipefish (Syngnathus leptorhynchus), saddleback gunnel (Pholis ornata), Pacific staghorn sculpin (Leptocottus armatus), and Pacific sand lance (Ammodytes personatus). Total catch and species richness were highest at the two locations closest to the urban center of Bellingham; however, species diversity and evenness were highest at the two eelgrass beds farthest from the city center. Descriptions of fish assemblages in eelgrass beds are expected to be useful in the development of future process-based investigations by study partners and will focus on the movements of sediments and contaminants and their influence on biota.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds1131","usgsCitation":"Andrews, M.I., and Liedtke, T.L., 2020, Fish assemblages in eelgrass beds of Bellingham Bay, Washington, Northern Puget Sound, 2019: U.S. Geological Survey Data Series 1131, 11 p., https://doi.org/10.3133/ds1131.","productDescription":"iv, 11 p.","onlineOnly":"Y","ipdsId":"IP-117153","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":379932,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/1131/ds1131.pdf","text":"Report","size":"2.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 1131"},{"id":379931,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/1131/coverthb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Bellingham Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.68020629882812,\n 48.45561965661709\n ],\n [\n -122.42752075195314,\n 48.45561965661709\n ],\n [\n -122.42752075195314,\n 48.79510425169179\n ],\n [\n -122.68020629882812,\n 48.79510425169179\n ],\n [\n -122.68020629882812,\n 48.45561965661709\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
Widespread application of neonicotinoids has led to their proliferation in waters. Despite low neonicotinoid hydrophobicity, our prior studies implicated granular activated carbon (GAC) in neonicotinoid removal. Based on known receptor binding characteristics, we hypothesized that the insecticidal pharmacophore influences neonicotinoid sorption. Our objectives were to illuminate drivers of neonicotinoid sorption for parent neonicotinoids (imidacloprid, clothianidin, thiamethoxam, and thiacloprid) and pharmacophore-altered metabolites (desnitro-imidacloprid and imidacloprid urea) to GAC, powdered activated carbon, and carbon nanotubes (CNTs). Neonicotinoid sorption to GAC was extensive and largely irreversible, with significantly greater sorption of imidacloprid than desnitro-imidacloprid. Imidacloprid and imidacloprid urea (electronegative pharmacophores) sorbed most extensively to nonfunctionalized CNTs, whereas desnitro-imidacloprid (positive pharmacophore) sorbed most to COOH-CNTs, indicating the importance of charge interactions and/or hydrogen bonding between the pharmacophore and carbon surface. Water chemistry parameters (temperature, alkalinity, ionic strength, and humic acid) inhibited overall neonicotinoid sorption, suggesting that pharmacophore-driven sorption in real waters may be diminished. Analysis of a full-scale drinking water treatment plant GAC filter influent, effluent, and spent GAC attributes neonicotinoid/metabolite removal to GAC under real-world conditions for the first time. Our results demonstrate that the neonicotinoid pharmacophore not only confers insecticide selectivity but also impacts sorption behavior, leading to less effective removal of metabolites by GAC filters in water treatment.
","language":"English","publisher":"American Chemical Society","doi":"10.1021/acs.est.0c04187","usgsCitation":"Webb, D.T., Nagorzanski, M.R., Powers, M.M., Cwiertny, D.M., Hladik, M.L., and LeFevre, G.H., 2020, Differences in neonicotinoid and metabolite sorption to activated carbon are driven by alterations to the insecticidal pharmacophore: Environmental Science and Technology, v. 54, no. 22, p. 14694-14705, https://doi.org/10.1021/acs.est.0c04187.","productDescription":"10 p.","startPage":"14694","endPage":"14705","onlineOnly":"N","ipdsId":"IP-119721","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":379964,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"54","issue":"22","noUsgsAuthors":false,"publicationDate":"2020-10-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Webb, Danielle T.","contributorId":211879,"corporation":false,"usgs":false,"family":"Webb","given":"Danielle","email":"","middleInitial":"T.","affiliations":[{"id":6768,"text":"University of Iowa","active":true,"usgs":false}],"preferred":false,"id":803520,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nagorzanski, Matthew R.","contributorId":211881,"corporation":false,"usgs":false,"family":"Nagorzanski","given":"Matthew","email":"","middleInitial":"R.","affiliations":[{"id":6768,"text":"University of Iowa","active":true,"usgs":false}],"preferred":false,"id":803521,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Powers, Megan M","contributorId":244212,"corporation":false,"usgs":false,"family":"Powers","given":"Megan","email":"","middleInitial":"M","affiliations":[{"id":6768,"text":"University of Iowa","active":true,"usgs":false}],"preferred":false,"id":803522,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cwiertny, David M.","contributorId":190557,"corporation":false,"usgs":false,"family":"Cwiertny","given":"David","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":803523,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hladik, Michelle L. 0000-0002-0891-2712","orcid":"https://orcid.org/0000-0002-0891-2712","contributorId":205314,"corporation":false,"usgs":true,"family":"Hladik","given":"Michelle","middleInitial":"L.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":803524,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"LeFevre, Gregory H.","contributorId":211880,"corporation":false,"usgs":false,"family":"LeFevre","given":"Gregory","email":"","middleInitial":"H.","affiliations":[{"id":6768,"text":"University of Iowa","active":true,"usgs":false}],"preferred":true,"id":803525,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70215981,"text":"70215981 - 2020 - Harvester ant seed removal in an invaded sagebrush ecosystem: Implications for restoration","interactions":[],"lastModifiedDate":"2020-12-29T21:46:00.683246","indexId":"70215981","displayToPublicDate":"2020-10-29T08:11:31","publicationYear":"2020","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":"Harvester ant seed removal in an invaded sagebrush ecosystem: Implications for restoration","docAbstract":"A better understanding of seed movement in plant community dynamics is needed, especially in light of disturbance‐driven changes and investments into restoring degraded plant communities. A primary agent of change within the sagebrush‐steppe is wildfire and invasion by non‐native forbs and grasses, primarily cheatgrass (Bromus tectorum). Our objectives were to quantify seed removal and evaluate ecological factors influencing seed removal within degraded sagebrush‐steppe by granivorous Owyhee harvester ants (Pogonomyrmex salinus Olsen). In 2014, we sampled 76 harvester ant nests across 11 plots spanning a gradient of cheatgrass invasion (40%–91% cover) in southwestern Idaho, United States. We presented seeds from four plant species commonly used in postfire restoration at 1.5 and 3.0 m from each nest to quantify seed removal. We evaluated seed selection for presented species, monthly removal, and whether biotic and abiotic factors (e.g., distance to nearest nest, temperature) influenced seed removal. Our top model indicated seed removal was positively correlated with nest height, an indicator of colony size. Distance to seeds and cheatgrass canopy cover reduced seed removal, likely due to increased search and handling time. Harvester ants were selective, removing Indian ricegrass (Achnatherum hymenoides) more than any other species presented. We suspect this was due to ease of seed handling and low weight variability. Nest density influenced monthly seed removal, as we estimated monthly removal of 1,890 seeds for 0.25 ha plots with 1 nest and 29,850 seeds for plots with 15 nests. Applying monthly seed removal to historical restoration treatments across the western United States showed harvester ants can greatly reduce seed availability at degraded sagebrush sites; for instance, fourwing saltbush (Atriplex canescens) seeds could be removed in <2 months. Collectively, these results shed light on seed removal by harvester ants and emphasize their potential influence on postfire restoration within invaded sagebrush communities.
Plant productivity is central to numerous ecosystem functions in tidal wetlands. We examined how productivity of brackish marsh plants in northern California responded to abiotic stress gradients of inundation and salinity using two experimental approaches. In a greenhouse study with varying salinity, shoot production and biomass of Juncus balticus, Schoenoplectus acutus and S. americanus all declined monotonically with higher salinity, with evidence of differences in sensitivity among species by their varied functional responses. Salinity also negatively affected fecundity for the one species (S. americanus) that produced enough inflorescences during the experiment for analysis. In a field manipulation of inundation and initial pore water salinity, total end-of-season biomass and other metrics of growth in the high marsh species, J. balticus, had unimodal relationships with inundation. Root production tended to be greater strongly impacted by greater inundation than shoot production. The salinity treatment quickly dissipated for treatments that were flooded more frequently but persisted at a higher marsh elevation where it suppressed plant growth. These results suggest that both increased flooding and salinity associated with climate change and sea-level rise may negatively impact productivity of brackish marsh species, but with variable effects by species and stressor.
","language":"English","publisher":"Springer","doi":"10.1007/s10750-020-04419-3","usgsCitation":"Janousek, C.N., Dugger, B.D., Drucker, B.M., and Thorne, K., 2020, Salinity and inundation effects on productivity of brackish tidal marsh plants in the San Francisco Bay-Delta Estuary: Hydrobiologia, v. 847, p. 4311-4323, https://doi.org/10.1007/s10750-020-04419-3.","productDescription":"13 p.","startPage":"4311","endPage":"4323","ipdsId":"IP-122239","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":385759,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","city":"San Francisco","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.134765625,\n 36.84446074079564\n ],\n [\n -120.9814453125,\n 36.84446074079564\n ],\n [\n -120.9814453125,\n 39.232253141714885\n ],\n [\n -123.134765625,\n 39.232253141714885\n ],\n [\n -123.134765625,\n 36.84446074079564\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"847","noUsgsAuthors":false,"publicationDate":"2020-10-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Janousek, Christopher N. 0000-0003-2124-6715","orcid":"https://orcid.org/0000-0003-2124-6715","contributorId":103951,"corporation":false,"usgs":false,"family":"Janousek","given":"Christopher","email":"","middleInitial":"N.","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":815986,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dugger, Bruce D.","contributorId":176167,"corporation":false,"usgs":false,"family":"Dugger","given":"Bruce","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":815987,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Drucker, Brandon M","contributorId":258214,"corporation":false,"usgs":false,"family":"Drucker","given":"Brandon","email":"","middleInitial":"M","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":815988,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thorne, Karen M. 0000-0002-1381-0657","orcid":"https://orcid.org/0000-0002-1381-0657","contributorId":204579,"corporation":false,"usgs":true,"family":"Thorne","given":"Karen M.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":815989,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70216159,"text":"70216159 - 2020 - Detection and assessment of a large and potentially tsunamigenic periglacial landslide in Barry Arm, Alaska","interactions":[],"lastModifiedDate":"2023-11-02T16:54:18.814614","indexId":"70216159","displayToPublicDate":"2020-10-29T07:50:24","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Detection and assessment of a large and potentially tsunamigenic periglacial landslide in Barry Arm, Alaska","docAbstract":"The retreat of glaciers in response to global warming has the potential to trigger landslides in glaciated regions around the globe. Landslides that enter fjords or lakes can cause tsunamis, which endanger people and infrastructure far from the landslide itself. Here we document the ongoing movement of an unstable slope (total volume of 455 million m3) in Barry Arm, a fjord in Prince William Sound, Alaska. The slope moved rapidly between 2010 and 2017, yielding a horizontal displacement of 120 m, which is highly correlated with the rapid retreat and thinning of Barry Glacier. Should the entire unstable slope collapse at once, preliminary tsunami modeling suggests a maximum runup of 300 m near the landslide, which may have devastating impacts on local communities. Our findings highlight the need for interdisciplinary studies of recently deglaciated fjords to refine our understanding of the impact of climate change on landslides and tsunamis.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2020GL089800","usgsCitation":"Dai, C., Higman, B., Lynett, P.J., Jacquemart, M., Howat, I., Liljedahl, A.K., Dufresne, A., Freymueller, J.T., Geertsema, M., Jones, M.W., and Haeussler, P., 2020, Detection and assessment of a large and potentially tsunamigenic periglacial landslide in Barry Arm, Alaska: Geophysical Research Letters, e2020GL089800, 9 p., https://doi.org/10.1029/2020GL089800.","productDescription":"e2020GL089800, 9 p.","ipdsId":"IP-122213","costCenters":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"links":[{"id":454932,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2020gl089800","text":"Publisher Index Page"},{"id":380255,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Barry Arm","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -148.18436382537658,\n 61.20521067964421\n ],\n [\n -148.18436382537658,\n 61.11202000604544\n ],\n [\n -148.0222489470055,\n 61.11202000604544\n ],\n [\n -148.0222489470055,\n 61.20521067964421\n ],\n [\n -148.18436382537658,\n 61.20521067964421\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationDate":"2020-11-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Dai, Chunli 0000-0003-1840-8699","orcid":"https://orcid.org/0000-0003-1840-8699","contributorId":244604,"corporation":false,"usgs":false,"family":"Dai","given":"Chunli","email":"","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":804250,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Higman, Bretwood","contributorId":224587,"corporation":false,"usgs":false,"family":"Higman","given":"Bretwood","affiliations":[{"id":40893,"text":"Ground Truth Trekking, Seldovia, AK, USA","active":true,"usgs":false}],"preferred":false,"id":804251,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lynett, Patrick J. 0000-0002-2856-9405","orcid":"https://orcid.org/0000-0002-2856-9405","contributorId":244605,"corporation":false,"usgs":false,"family":"Lynett","given":"Patrick","email":"","middleInitial":"J.","affiliations":[{"id":13249,"text":"University of Southern California","active":true,"usgs":false}],"preferred":false,"id":804252,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jacquemart, Mylene 0000-0003-2501-7645","orcid":"https://orcid.org/0000-0003-2501-7645","contributorId":244606,"corporation":false,"usgs":false,"family":"Jacquemart","given":"Mylene","email":"","affiliations":[{"id":36621,"text":"University of Colorado","active":true,"usgs":false}],"preferred":false,"id":804253,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Howat, Ian 0000-0002-8072-6260","orcid":"https://orcid.org/0000-0002-8072-6260","contributorId":244607,"corporation":false,"usgs":false,"family":"Howat","given":"Ian","email":"","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":804254,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Liljedahl, Anna K. 0000-0001-7114-6443","orcid":"https://orcid.org/0000-0001-7114-6443","contributorId":150135,"corporation":false,"usgs":false,"family":"Liljedahl","given":"Anna","email":"","middleInitial":"K.","affiliations":[{"id":6695,"text":"UAF","active":true,"usgs":false}],"preferred":false,"id":804255,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Dufresne, Anja 0000-0001-7777-3317","orcid":"https://orcid.org/0000-0001-7777-3317","contributorId":244608,"corporation":false,"usgs":false,"family":"Dufresne","given":"Anja","email":"","affiliations":[{"id":48946,"text":"Aachen University, Germany","active":true,"usgs":false}],"preferred":false,"id":804256,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Freymueller, Jeffery T. 0000-0003-0614-0306","orcid":"https://orcid.org/0000-0003-0614-0306","contributorId":244609,"corporation":false,"usgs":false,"family":"Freymueller","given":"Jeffery","email":"","middleInitial":"T.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":804257,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Geertsema, Marten","contributorId":197464,"corporation":false,"usgs":false,"family":"Geertsema","given":"Marten","email":"","affiliations":[],"preferred":false,"id":804258,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Jones, Melissa Ward 0000-0002-3401-2515","orcid":"https://orcid.org/0000-0002-3401-2515","contributorId":244610,"corporation":false,"usgs":false,"family":"Jones","given":"Melissa","email":"","middleInitial":"Ward","affiliations":[{"id":16705,"text":"Woods Hole Research Center","active":true,"usgs":false}],"preferred":false,"id":804259,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Haeussler, Peter J. 0000-0002-1503-6247","orcid":"https://orcid.org/0000-0002-1503-6247","contributorId":219956,"corporation":false,"usgs":true,"family":"Haeussler","given":"Peter J.","affiliations":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":804260,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70222578,"text":"70222578 - 2020 - On the size of the flare associated with the solar proton event in 774 AD","interactions":[],"lastModifiedDate":"2021-08-05T12:52:31.307","indexId":"70222578","displayToPublicDate":"2020-10-29T07:48:31","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":917,"text":"Astrophysical Journal","active":true,"publicationSubtype":{"id":10}},"title":"On the size of the flare associated with the solar proton event in 774 AD","docAbstract":"The 774 AD solar proton event (SPE) detected in cosmogenic nuclides had an inferred >1 GV (>430 MeV) fluence estimated to have been ~30–70 times larger than that of the 1956 February 23 ground level event (GLE). The 1956 GLE was itself ~2.5 times larger at >430 MeV than the episode of strong GLE activity from 1989 August–October. We use an inferred soft X-ray (SXR) class of X20 ± 10 for the 1956 February 23 eruptive flare as a bridge to the source flare for the 774 SPE. A correlation of the >200 MeV proton fluences of hard-spectra post-1975 GLEs with the SXR peak fluxes of their associated flares yields an SXR flare class of X285 ± 140 (bolometric energy of ~(1.9 ± 0.7) × 1033 erg) for the 774 flare. This estimate is within theoretical determinations of the largest flare the Sun could produce based on the largest spot group yet observed. Assuming a single eruptive flare source for the 774 SPE, the above estimate indicates that the Sun can produce a threshold-level 1033 erg superflare. If the 774 event originated in two closely timed, equal-fluence SPEs, the inferred flare size drops to X180 ± 90 (~(1.4 ± 0.5) × 1033 erg). We speculate on favorable solar conditions that can lead to enhanced shock acceleration of high-energy protons in eruptive flares.
","language":"English","publisher":"American Astronomical Society","doi":"10.3847/1538-4357/abad93","usgsCitation":"Cliver, E., Hayakawa, H., Love, J.J., and Neidig, D.F., 2020, On the size of the flare associated with the solar proton event in 774 AD: Astrophysical Journal, v. 903, no. 1, https://doi.org/10.3847/1538-4357/abad93.","ipdsId":"IP-120688","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":454933,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3847/1538-4357/abad93","text":"Publisher Index Page"},{"id":387711,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"903","issue":"1","noUsgsAuthors":false,"publicationDate":"2020-10-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Cliver, E. W. 0000-0002-4342-6728","orcid":"https://orcid.org/0000-0002-4342-6728","contributorId":261774,"corporation":false,"usgs":false,"family":"Cliver","given":"E. W.","affiliations":[{"id":53008,"text":"School of Physics & Astronomy, University of Glasgow, Glasgow G12 8QQ, UK National Solar Observatory, 3665 Discovery Drive, Boulder, CO, 80304, USA","active":true,"usgs":false}],"preferred":false,"id":820617,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hayakawa, H. 0000-0001-5370-3365","orcid":"https://orcid.org/0000-0001-5370-3365","contributorId":261775,"corporation":false,"usgs":false,"family":"Hayakawa","given":"H.","email":"","affiliations":[{"id":53009,"text":"Nagoya University, Rutherford Appleton Laboratory, Nishina Center","active":true,"usgs":false}],"preferred":false,"id":820618,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Love, Jeffrey J. 0000-0002-3324-0348 jlove@usgs.gov","orcid":"https://orcid.org/0000-0002-3324-0348","contributorId":760,"corporation":false,"usgs":true,"family":"Love","given":"Jeffrey","email":"jlove@usgs.gov","middleInitial":"J.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":820619,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Neidig, D. F.","contributorId":261776,"corporation":false,"usgs":false,"family":"Neidig","given":"D.","email":"","middleInitial":"F.","affiliations":[{"id":53010,"text":"U.S. Air Force Research Laboratory (retired)","active":true,"usgs":false}],"preferred":false,"id":820620,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70215985,"text":"70215985 - 2020 - Nitrate in streams during winter low‐flow conditions as an indicator of legacy nitrate","interactions":[],"lastModifiedDate":"2020-11-30T16:30:57.387972","indexId":"70215985","displayToPublicDate":"2020-10-29T07:48:13","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Nitrate in streams during winter low‐flow conditions as an indicator of legacy nitrate","docAbstract":"Winter low‐flow (LF) conditions in streams provide a potential opportunity to evaluate the importance of legacy nitrate in catchments due to the dominance of slow‐flow transport pathways and lowered biotic activity. In this study, the concentration, flux, and trend of nitrate in streams during winter low‐flow conditions were analyzed at 320 sites in the conterminous United States. LF flow‐normalized nitrate concentrations varied from <0.1 to >20 mg‐N L‐1 and LF conditions contributed between 2% and 98% of the winter nitrate flux. LF nitrate concentrations generally exceeded 2.5 mg‐N L‐1 in the upper Midwest, with smaller regions of high LF nitrate concentrations in eastern Texas and along the northern mid‐Atlantic coast. Groundwater was inferred to be the primary or sole contributor of nitrate to streams during winter LF conditions at 140 of our 320 sites. Among these 140 sites, nitrate from groundwater comprised 45% or more of the winter nitrate flux at a quarter of the sites. Among the same 140 sites, concentrations of nitrate in streams during winter LF conditions generally increased between 2002 and 2012 at sites where 40% or more of the winter flux was from groundwater, suggesting that concentrations of nitrate in the contributing groundwater system were increasing. Using metrics developed herein, we characterize the potential importance of legacy nitrate at sites in this study and discuss methods to characterize sites with fewer samples than required by our models or at sites without continuous stream discharge measurements.
Modeling forest change effects on snow is critical to resource management. However, many models either do not appropriately model canopy structure or cannot represent fine‐scale changes in structure following a disturbance. We applied a 1 m2 resolution energy budget snowpack model at a forested site in New Mexico, USA, affected by a wildfire, using input data from lidar to represent prefire and postfire canopy conditions. Both scenarios were forced with 37 years of equivalent meteorology to simulate the effect of fire‐mediated canopy change on snowpack under varying meteorology. Postfire, the simulated snow distribution was substantially altered, and despite an overall increase in snow, 32% of the field area displayed significant decreases, resulting in higher snowpack variability. The spatial differences in snow were correlated with the change in several direction‐based forest structure metrics (aspect‐based canopy edginess and gap area). Locations with decreases in snow following the fire were on southern aspects that transitioned to south facing canopy edges, canopy gaps that increased in size to the south, or where large trees were removed. Locations with largest increases in snow occurred where all canopy was removed. Changes in canopy density metrics, typically used in snow models to represent the forest, did not fully explain the effects of fire on snow distribution. This explains why many models are not able to represent greater postfire variability in snow distribution and tend to predict only increases in snowpack following a canopy disturbance event despite observational studies showing both increases and decreases.
In this synthesis, we assess present research and anticipate future development needs in modeling water quality in watersheds. We first discuss areas of potential improvement in the representation of freshwater systems pertaining to water quality, including representation of environmental interfaces, in‐stream water quality and process interactions, soil health and land management, and (peri‐)urban areas. In addition, we provide insights into the contemporary challenges in the practices of watershed water quality modeling, including quality control of monitoring data, model parameterization and calibration, uncertainty management, scale mismatches, and provisioning of modeling tools. Finally, we make three recommendations to provide a path forward for improving watershed water quality modeling science, infrastructure, and practices. These include building stronger collaborations between experimentalists and modelers, bridging gaps between modelers and stakeholders, and cultivating and applying procedural knowledge to better govern and support water quality modeling processes within organizations.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2020WR027721","usgsCitation":"Fu, B., Horsburgh, J., Jakeman, A.J., Gaultieri, C., Arnold, T.W., Marshall, L.A., Green, T.R., Quinn, N.W., Volk, M., Hunt, R., Vezzaro, L., Croke, B., Jakeman, J., Snow, V.O., and Rashleigh, B., 2020, Modeling water quality in watersheds: From here to the next generation: Water Resources Research, v. 56, no. 11, e2020WR027721, 28 p., https://doi.org/10.1029/2020WR027721.","productDescription":"e2020WR027721, 28 p.","ipdsId":"IP-123332","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":454942,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2020wr027721","text":"Publisher Index Page"},{"id":383140,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"56","issue":"11","noUsgsAuthors":false,"publicationDate":"2020-11-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Fu, Baihua 0000-0003-2494-0518","orcid":"https://orcid.org/0000-0003-2494-0518","contributorId":174165,"corporation":false,"usgs":false,"family":"Fu","given":"Baihua","email":"","affiliations":[],"preferred":false,"id":810074,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Horsburgh, J. S. 0000-0002-0768-3196","orcid":"https://orcid.org/0000-0002-0768-3196","contributorId":248851,"corporation":false,"usgs":false,"family":"Horsburgh","given":"J. S.","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":810075,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jakeman, Anthony J. 0000-0001-5282-2215","orcid":"https://orcid.org/0000-0001-5282-2215","contributorId":173848,"corporation":false,"usgs":false,"family":"Jakeman","given":"Anthony","email":"","middleInitial":"J.","affiliations":[{"id":17939,"text":"The Australian National University","active":true,"usgs":false}],"preferred":false,"id":810076,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gaultieri, C 0000-0002-3717-1618","orcid":"https://orcid.org/0000-0002-3717-1618","contributorId":248852,"corporation":false,"usgs":false,"family":"Gaultieri","given":"C","email":"","affiliations":[{"id":50045,"text":"University of Napoli","active":true,"usgs":false}],"preferred":false,"id":810077,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Arnold, Todd W.","contributorId":36058,"corporation":false,"usgs":false,"family":"Arnold","given":"Todd","email":"","middleInitial":"W.","affiliations":[{"id":12644,"text":"University of Minnesota, St. Paul","active":true,"usgs":false}],"preferred":false,"id":810078,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Marshall, Lucy A. 0000-0003-0450-4292","orcid":"https://orcid.org/0000-0003-0450-4292","contributorId":198080,"corporation":false,"usgs":false,"family":"Marshall","given":"Lucy","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":810079,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Green, Tim R 0000-0002-1441-8008","orcid":"https://orcid.org/0000-0002-1441-8008","contributorId":248853,"corporation":false,"usgs":false,"family":"Green","given":"Tim","email":"","middleInitial":"R","affiliations":[{"id":39550,"text":"U.S. Department of Agriculture, Agricultural Research Service","active":true,"usgs":false}],"preferred":false,"id":810080,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Quinn, Nigel W. T. 0000-0003-3333-4763","orcid":"https://orcid.org/0000-0003-3333-4763","contributorId":248854,"corporation":false,"usgs":false,"family":"Quinn","given":"Nigel","email":"","middleInitial":"W. T.","affiliations":[{"id":38900,"text":"Lawrence Berkeley National Laboratory","active":true,"usgs":false}],"preferred":false,"id":810081,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Volk, Martin 0000-0003-0064-8133","orcid":"https://orcid.org/0000-0003-0064-8133","contributorId":247479,"corporation":false,"usgs":false,"family":"Volk","given":"Martin","email":"","affiliations":[{"id":13477,"text":"Washington Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":810082,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Hunt, Randall J. 0000-0001-6465-9304","orcid":"https://orcid.org/0000-0001-6465-9304","contributorId":16118,"corporation":false,"usgs":true,"family":"Hunt","given":"Randall J.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":810083,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Vezzaro, L. 0000-0001-6344-7131","orcid":"https://orcid.org/0000-0001-6344-7131","contributorId":248855,"corporation":false,"usgs":false,"family":"Vezzaro","given":"L.","affiliations":[{"id":50046,"text":"Technical University of Denmark","active":true,"usgs":false}],"preferred":false,"id":810084,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Croke, Barry 0000-0001-9216-1554","orcid":"https://orcid.org/0000-0001-9216-1554","contributorId":248856,"corporation":false,"usgs":false,"family":"Croke","given":"Barry","email":"","affiliations":[{"id":27305,"text":"Australia National University","active":true,"usgs":false}],"preferred":false,"id":810085,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Jakeman, John 0000-0002-3517-337X","orcid":"https://orcid.org/0000-0002-3517-337X","contributorId":248857,"corporation":false,"usgs":false,"family":"Jakeman","given":"John","email":"","affiliations":[{"id":34829,"text":"Sandia National Laboratories","active":true,"usgs":false}],"preferred":false,"id":810086,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Snow, Valerie O 0000-0002-6911-8184","orcid":"https://orcid.org/0000-0002-6911-8184","contributorId":248846,"corporation":false,"usgs":false,"family":"Snow","given":"Valerie","email":"","middleInitial":"O","affiliations":[{"id":50044,"text":"AgResearch","active":true,"usgs":false}],"preferred":false,"id":810087,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Rashleigh, Brenda 0000-0002-0806-686X","orcid":"https://orcid.org/0000-0002-0806-686X","contributorId":242708,"corporation":false,"usgs":false,"family":"Rashleigh","given":"Brenda","email":"","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":810088,"contributorType":{"id":1,"text":"Authors"},"rank":15}]}} ,{"id":70228467,"text":"70228467 - 2020 - Keeping up with the times: Mapping range-wide habitat suitability for endangered species in a changing environment","interactions":[],"lastModifiedDate":"2022-02-14T12:04:27.764111","indexId":"70228467","displayToPublicDate":"2020-10-28T11:13:53","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1015,"text":"Biological Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Keeping up with the times: Mapping range-wide habitat suitability for endangered species in a changing environment","docAbstract":"Biologists and policy-makers have the difficult task of allocating limited resources to habitat conservation and management for endangered species in the face of changing environmental conditions. Satellite remote sensing can inform conservation because it is an efficient means to obtain environmental data over broad spatial and temporal extents. Yet, the challenges of accessing, processing, and analyzing remote sensing data hinder wider application of these techniques in conservation planning. We used Landsat data and hierarchical statistical models to link satellite-derived habitat measurements with abundance of endangered Yuma Ridgway's rails (Rallus obsoletus yumanensis) within the Lower Colorado River Basin and Salton Sink, USA. We addressed many of the challenges facing the application of remote sensing techniques by using the web-based, freely-available Google Earth Engine to process Landsat datasets, apply habitat models, and generate maps to predict habitat suitability at a fine spatial grain (30 m) across the range of the species. These maps are shareable, interactive, and easy to update annually as habitat conditions change using a Google Earth Engine App we developed. Thus, we provide a framework for building habitat suitability models and maps to help target adaptive habitat management over broad extents for sensitive species, enabling biologists to improve conservation and restoration efforts regularly as conditions change in highly variable ecosystems. We demonstrate this approach for Yuma Ridgway's rails, but our methods for merging hierarchical statistical models with open-source mapping software to describe spatial-temporal heterogeneity in habitat quality are applicable to any species, and are especially helpful to species inhabiting highly variable ecosystems.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.biocon.2020.108734","usgsCitation":"Harrity, E.J., Stevens, B., and Conway, C.J., 2020, Keeping up with the times: Mapping range-wide habitat suitability for endangered species in a changing environment: Biological Conservation, v. 250, 108734,10 p., https://doi.org/10.1016/j.biocon.2020.108734.","productDescription":"108734,10 p.","ipdsId":"IP-116214","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":395854,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Mexico, United States","state":"Arizona, California, Nevada","otherGeospatial":"Colorado River Basin, Salton Sink","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.840087890625,\n 32.52828936482526\n ],\n [\n -114.796142578125,\n 32.44024912337551\n ],\n [\n -114.08752441406249,\n 32.697177359290635\n ],\n [\n -114.246826171875,\n 33.55055114384406\n ],\n [\n -114.29077148437499,\n 33.8247936182649\n ],\n [\n -113.873291015625,\n 34.31621838080741\n ],\n [\n -114.356689453125,\n 34.88593094075317\n ],\n [\n -114.63134765625001,\n 34.858890491257796\n ],\n [\n -115.916748046875,\n 33.128351191631566\n ],\n [\n -114.840087890625,\n 32.52828936482526\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"250","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Harrity, Eamon J.","contributorId":275852,"corporation":false,"usgs":false,"family":"Harrity","given":"Eamon","email":"","middleInitial":"J.","affiliations":[{"id":39599,"text":"ui","active":true,"usgs":false}],"preferred":false,"id":834366,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stevens, Bryan S.","contributorId":275853,"corporation":false,"usgs":false,"family":"Stevens","given":"Bryan S.","affiliations":[{"id":39599,"text":"ui","active":true,"usgs":false}],"preferred":false,"id":834367,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Conway, Courtney J. 0000-0003-0492-2953 cconway@usgs.gov","orcid":"https://orcid.org/0000-0003-0492-2953","contributorId":2951,"corporation":false,"usgs":true,"family":"Conway","given":"Courtney","email":"cconway@usgs.gov","middleInitial":"J.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":834365,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70216654,"text":"70216654 - 2020 - Modest residual effects of short-term warming, altered hydration, and biocrust successional state on dryland soil heterotrophic carbon and nitrogen cycling","interactions":[],"lastModifiedDate":"2020-11-27T17:09:15.373856","indexId":"70216654","displayToPublicDate":"2020-10-28T11:04:58","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7439,"text":"Frontiers in Ecology and Evolution Section Biogeography and Macroecology","active":true,"publicationSubtype":{"id":10}},"title":"Modest residual effects of short-term warming, altered hydration, and biocrust successional state on dryland soil heterotrophic carbon and nitrogen cycling","docAbstract":"Biological soil crusts (biocrusts) on the Colorado Plateau may fuel carbon (C) and nitrogen (N) cycling of soil heterotrophic organisms throughout the region. Late successional moss and lichen biocrusts, in particular, can increase soil C and N availability, but some data suggest these biocrust types will be replaced by early successional cyanobacterial biocrusts as the region undergoes warming and aridification. In this study, we evaluated the short-term interactive effects of biocrust successional state and elevated temperature on soil heterotrophic C and N cycling (specifically, soil respiration, N2O emissions, microbial biomass C and N, and soluble C and N). We collected soils following an 87-day greenhouse mesocosm experiment where the soils had been topped with different biocrust successional states (moss-dominated, cyanobacteria-dominated, or no biocrust) and had experienced different temperatures (ambient and warmed), under an artificial precipitation regime. Following this pre-incubation mesocosm phase, the soils were assessed using a short-term (2-day) laboratory incubation to determine the cumulative effect of the elevated temperature and altered biocrust successional state on the temperature sensitivity of soil heterotrophic C and N cycling. We found that there were interactive effects of biocrust successional state and exposure to warmer temperatures during the mesocosm phase under greenhouse conditions on the rate and temperature sensitivity of soil heterotrophic C and N cycling in laboratory incubations. Soils collected from beneath late successional biocrusts exhibited higher C and N cycling rates than those from beneath early successional crusts, while warming reduced both the magnitude and the temperature sensitivity of C and N cycling. The inhibiting effect of warming, was most evident in soils from beneath late successional biocrusts, which, during the mesocosm phase, also exhibited the greatest reductions in gross primary production and respiration in response to the warming treatment. Taken together, these data suggest that an overall effect of climate warming may be increasing resource limitation of the soil heterotrophic C and N cycles in the region, which may magnify alterations associated with the changes in biocrust community structure documented in previous studies. Overall, results from this study suggest that soil heterotrophic biogeochemical cycling is affected by interactions between temperature and the biocrust community that lives atop the mineral soil, with important implications for C and N cycling into the future.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/fevo.2020.467157","usgsCitation":"Tucker, C., Ferrenberg, S., and Reed, S., 2020, Modest residual effects of short-term warming, altered hydration, and biocrust successional state on dryland soil heterotrophic carbon and nitrogen cycling: Frontiers in Ecology and Evolution Section Biogeography and Macroecology, v. 8, 467157, 17 p., https://doi.org/10.3389/fevo.2020.467157.","productDescription":"467157, 17 p.","ipdsId":"IP-110869","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":454945,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fevo.2020.467157","text":"Publisher Index Page"},{"id":380845,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nevada","city":"Castle Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -109.66140747070312,\n 38.50519140240356\n ],\n [\n -109.26040649414062,\n 38.50519140240356\n ],\n [\n -109.26040649414062,\n 38.78085193143006\n ],\n [\n -109.66140747070312,\n 38.78085193143006\n ],\n [\n -109.66140747070312,\n 38.50519140240356\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"8","noUsgsAuthors":false,"publicationDate":"2020-10-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Tucker, Colin 0000-0002-4539-7780 ctucker@usgs.gov","orcid":"https://orcid.org/0000-0002-4539-7780","contributorId":167487,"corporation":false,"usgs":true,"family":"Tucker","given":"Colin","email":"ctucker@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":805739,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ferrenberg, Scott","contributorId":217143,"corporation":false,"usgs":false,"family":"Ferrenberg","given":"Scott","affiliations":[{"id":39569,"text":"Department of Biology, New Mexico State University, Las Cruces, NM 88001, USA","active":true,"usgs":false}],"preferred":false,"id":805740,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Reed, Sasha C. 0000-0002-8597-8619","orcid":"https://orcid.org/0000-0002-8597-8619","contributorId":205372,"corporation":false,"usgs":true,"family":"Reed","given":"Sasha C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":805741,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70255170,"text":"70255170 - 2020 - Daily nest predation rates decrease with body size in passerine birds","interactions":[],"lastModifiedDate":"2024-06-13T14:46:53.839237","indexId":"70255170","displayToPublicDate":"2020-10-28T09:42:17","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5500,"text":"The American Naturalist","onlineIssn":"1537-5323","printIssn":" 0003-014","active":true,"publicationSubtype":{"id":10}},"title":"Daily nest predation rates decrease with body size in passerine birds","docAbstract":"Body size evolution is generally framed by the benefits of being large, while costs are largely overlooked. An important putative cost of being large is the need to extend development periods, which should increase exposure to predation and potentially select against larger size. In birds, this selection pressure can be important because predation is the main source of offspring mortality and predators should more readily detect the larger nests associated with larger body sizes. Here, we show for diverse passerine birds across the world that counter to expectations, larger species suffer lower daily nest predation rates than smaller species. This pattern is consistent despite latitudinal variation in predation and does not seem to reflect a tendency of larger species to use more protected nests or less exposed nest locations. Evidence instead suggests that larger species attack a wider array of predator sizes, which could reduce predation rates in nests of large-bodied species. Regardless of the mechanism, the lower daily nest predation rates of larger species yield slightly lower predation rates over the entire development period compared with smaller species. These results highlight the importance of behavior as a mechanism to alter selection pressures and have implications for body size evolution.
","language":"English","publisher":"University of Chicago Press","doi":"10.1086/711413","usgsCitation":"Unzeta, M., Martin, T.E., and Sol, D., 2020, Daily nest predation rates decrease with body size in passerine birds: The American Naturalist, v. 196, no. 6, p. 743-754, https://doi.org/10.1086/711413.","productDescription":"12 p.","startPage":"743","endPage":"754","ipdsId":"IP-113054","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":430136,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"196","issue":"6","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Unzeta, Mar","contributorId":338887,"corporation":false,"usgs":false,"family":"Unzeta","given":"Mar","email":"","affiliations":[{"id":81202,"text":"creaf","active":true,"usgs":false}],"preferred":false,"id":903655,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Martin, Thomas E. 0000-0002-4028-4867 tmartin@usgs.gov","orcid":"https://orcid.org/0000-0002-4028-4867","contributorId":1208,"corporation":false,"usgs":true,"family":"Martin","given":"Thomas","email":"tmartin@usgs.gov","middleInitial":"E.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":903654,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sol, Daniel","contributorId":338888,"corporation":false,"usgs":false,"family":"Sol","given":"Daniel","email":"","affiliations":[{"id":81202,"text":"creaf","active":true,"usgs":false}],"preferred":false,"id":903656,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70216386,"text":"70216386 - 2020 - Mussel community assessment tool for the Upper Mississippi River system","interactions":[],"lastModifiedDate":"2020-11-13T14:53:45.631508","indexId":"70216386","displayToPublicDate":"2020-10-28T08:47:52","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5254,"text":"Freshwater Mollusk Biology and Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Mussel community assessment tool for the Upper Mississippi River system","docAbstract":"Upper Mississippi River (UMR) resource managers need a quantitative means of evaluating the health of mussel assemblages to measure effects of management and regulatory actions, assess restoration techniques, and inform regulatory tasks. Our objective was to create a mussel community assessment tool (MCAT), consisting of a suite of metrics and scoring criteria, to consistently compare the relative health of UMR mussel assemblages. We developed an initial MCAT using quantitative data from 25 sites and 10 metrics. Metrics fell in five broad groups: conservation status and environmental sensitivity, taxonomic composition, population processes, abundance, and diversity. Metric scoring categories were based on quartile analysis: 25% scoring as good, 50% scoring as fair, and 25% scoring as poor. Scores were meant to facilitate establishing management priorities and mitigation options for the conservation of mussels. Scoring categories assumed that a healthy mussel assemblage consists of species with a variety of reproductive and life-history strategies, a low percentage of tolerant species, and a high percentage of sensitive species; shows evidence of adequate recruitment, a variety of age classes, and low mortality; and has high abundance, species richness, and species and tribe evenness. Metrics were validated using a modified Delphi technique. MCAT metrics generally reflected the professional opinions of UMR resource managers and provided a consistent evaluation technique with uniform definitions that managers could use to evaluate mussel assemblages. Additional data sets scored a priori by UMR resource managers were used to further validate metrics, resulting in data from 33 sites spanning over 980 km of the UMR. Initial and revised MCAT scores were similar, indicating that data represent the range of mussel assemblages in the UMR. Mussel assemblages could be evaluated using individual metrics or a composite score to suit management purposes. With additional data, metrics could be calibrated on a local scale or applied to other river systems.
","language":"English","publisher":"BioOne","doi":"10.31931/fmbc.v23i2.2020.109-123","usgsCitation":"Dunn, H.L., Zigler, S.J., and Newton, T., 2020, Mussel community assessment tool for the Upper Mississippi River system: Freshwater Mollusk Biology and Conservation, v. 23, no. 2, p. 109-123, https://doi.org/10.31931/fmbc.v23i2.2020.109-123.","productDescription":"15 p.","startPage":"109","endPage":"123","ipdsId":"IP-100031","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":454949,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.31931/fmbc.v23i2.2020.109-123","text":"Publisher Index Page"},{"id":380503,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Illinois, Iowa, Minnesota, Missouri, Wisconsin","otherGeospatial":"Upper Mississippi River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.9560546875,\n 38.85682013474361\n ],\n [\n -90.3076171875,\n 39.13006024213511\n ],\n [\n -91.043701171875,\n 39.690280594818034\n ],\n [\n -91.307373046875,\n 40.26276066437183\n ],\n [\n -90.791015625,\n 41.1290213474951\n ],\n [\n -90.87890625,\n 41.31907562295139\n ],\n [\n -90.2197265625,\n 41.566141964768384\n ],\n [\n -89.9560546875,\n 42.032974332441405\n ],\n [\n -90.50537109375,\n 42.54498667313236\n ],\n [\n -90.59326171875,\n 42.70665956351041\n ],\n [\n -90.90087890624999,\n 42.867912483915305\n ],\n [\n -90.966796875,\n 43.16512263158296\n ],\n [\n -90.999755859375,\n 43.492782808225\n ],\n [\n -91.1865234375,\n 43.96909818325171\n ],\n [\n -91.790771484375,\n 44.35527821160296\n ],\n [\n -92.1533203125,\n 44.53567453241317\n ],\n [\n -92.779541015625,\n 44.87144275016589\n ],\n [\n -93.087158203125,\n 44.68427737181225\n ],\n [\n -92.2412109375,\n 44.315987905196906\n ],\n [\n -91.834716796875,\n 44.02442151965934\n ],\n [\n -91.5380859375,\n 43.8503744993026\n ],\n [\n -91.241455078125,\n 43.22118973298753\n ],\n [\n -91.25244140624999,\n 43.092960677116295\n ],\n [\n -91.1865234375,\n 42.71473218539458\n ],\n [\n -90.758056640625,\n 42.50450285299051\n ],\n [\n -90.3955078125,\n 42.09007006868398\n ],\n [\n -90.50537109375,\n 41.672911819602085\n ],\n [\n -91.19750976562499,\n 41.50034959128928\n ],\n [\n -91.29638671875,\n 41.19518982948959\n ],\n [\n -91.20849609375,\n 41.03793062246529\n ],\n [\n -91.395263671875,\n 40.73893324113601\n ],\n [\n -91.62597656249999,\n 40.413496049701955\n ],\n [\n -91.746826171875,\n 40.027614437486655\n ],\n [\n -91.483154296875,\n 39.42770738465604\n ],\n [\n -90.966796875,\n 39.172658670429946\n ],\n [\n -90.703125,\n 38.79690830348427\n ],\n [\n -89.9560546875,\n 38.85682013474361\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"23","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Dunn, Heidi L.","contributorId":244888,"corporation":false,"usgs":false,"family":"Dunn","given":"Heidi","email":"","middleInitial":"L.","affiliations":[{"id":49009,"text":"EcoAnalysts, Inc.","active":true,"usgs":false}],"preferred":false,"id":804848,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zigler, Steven J. 0000-0002-4153-0652 szigler@usgs.gov","orcid":"https://orcid.org/0000-0002-4153-0652","contributorId":2410,"corporation":false,"usgs":true,"family":"Zigler","given":"Steven","email":"szigler@usgs.gov","middleInitial":"J.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":804849,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Newton, Teresa 0000-0001-9351-5852 tnewton@usgs.gov","orcid":"https://orcid.org/0000-0001-9351-5852","contributorId":150098,"corporation":false,"usgs":true,"family":"Newton","given":"Teresa","email":"tnewton@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":804850,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70216104,"text":"70216104 - 2020 - Assessment of burrowing behavior of freshwater juvenile mussels in sediment","interactions":[],"lastModifiedDate":"2020-11-06T12:49:54.295425","indexId":"70216104","displayToPublicDate":"2020-10-28T08:23:54","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5254,"text":"Freshwater Mollusk Biology and Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Assessment of burrowing behavior of freshwater juvenile mussels in sediment","docAbstract":"Standard laboratory sediment toxicity methods have been adapted for conducting toxicity tests with juvenile freshwater mussels. However, studies looking at juvenile mussel burrowing behavior at the water-sediment interface are limited. Juvenile mussels burrow in sediment for the first 0 to 4 yr of life but also may inhabit the sediment-water interface. The objective of this study was to evaluate burrowing behavior of various species and ages of juvenile freshwater mussels in three control sediments: West Bearskin Lake, Spring River, and coarse commercial sand. Species tested included (1) Fatmucket (Lampsilis siliquoidea), (2) Notched Rainbow (Villosa constricta), (3) Washboard (Megalonaias nervosa), (4) Rainbow (Villosa iris), (5) Arkansas Fatmucket (Lampsilis powellii), and (6) Oregon Floater (Anodonta oregonensis). Greater than 95% of the mussels burrowed into test sediment within 15 min. Across species, life stage, and substrate type, most mussels were recovered from the upper layers of sediment (91% at a sediment depth of 3.4 mm or less), and only 2% of the mussels were recovered at a depth >5.1 mm. No mussels were recovered from a depth >6.8 mm. There was no difference in mussel burrowing depth at 4 h versus 24 h across species, age, and sediment type. Two ages of Fatmucket burrowed to a significantly greater depth in the West Bearskin Lake sediment compared to the Spring River sediment or Coarse Sand. However, there was no significant difference in mean depth across sediment type with the other five species of mussels tested. Based on species and age of mussels tested, juvenile mussels up to an age of at least 20 wk and a length of at least 5 mm readily burrow into sediment and likely would be exposed to contaminants in whole sediment and associated pore water throughout a laboratory sediment toxicity test.
","language":"English","publisher":"BioOne","doi":"10.31931/fmbc.v23i2.2020.69-81","usgsCitation":"Kemble, N.E., Besser, J.M., Steevens, J.A., and Hughes, J., 2020, Assessment of burrowing behavior of freshwater juvenile mussels in sediment: Freshwater Mollusk Biology and Conservation, v. 23, no. 2, p. 69-81, https://doi.org/10.31931/fmbc.v23i2.2020.69-81.","productDescription":"13 p.","startPage":"69","endPage":"81","ipdsId":"IP-105537","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":454951,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.31931/fmbc.v23i2.2020.69-81","text":"Publisher Index Page"},{"id":436739,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9NTLG30","text":"USGS data release","linkHelpText":"Burrowing behavior of freshwater mussels"},{"id":380186,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"23","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Kemble, Nile E. 0000-0002-3608-0538 nkemble@usgs.gov","orcid":"https://orcid.org/0000-0002-3608-0538","contributorId":2626,"corporation":false,"usgs":true,"family":"Kemble","given":"Nile","email":"nkemble@usgs.gov","middleInitial":"E.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":804103,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Besser, John M. 0000-0002-9464-2244 jbesser@usgs.gov","orcid":"https://orcid.org/0000-0002-9464-2244","contributorId":2073,"corporation":false,"usgs":true,"family":"Besser","given":"John","email":"jbesser@usgs.gov","middleInitial":"M.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":804104,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Steevens, Jeffery A. 0000-0003-3946-1229","orcid":"https://orcid.org/0000-0003-3946-1229","contributorId":207511,"corporation":false,"usgs":true,"family":"Steevens","given":"Jeffery","middleInitial":"A.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":804105,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hughes, Jamie P.","contributorId":244522,"corporation":false,"usgs":false,"family":"Hughes","given":"Jamie P.","affiliations":[{"id":48808,"text":"Veterans United, Columbia MO","active":true,"usgs":false}],"preferred":false,"id":804106,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70216063,"text":"70216063 - 2020 - Topographic, soil, and climate drivers of drought sensitivity in forests and shrublands of the Pacific Northwest, USA","interactions":[],"lastModifiedDate":"2020-11-04T13:28:33.960827","indexId":"70216063","displayToPublicDate":"2020-10-28T07:24:42","publicationYear":"2020","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":"Topographic, soil, and climate drivers of drought sensitivity in forests and shrublands of the Pacific Northwest, USA","docAbstract":"Climate change is anticipated to increase the frequency and intensity of droughts, with major impacts to ecosystems globally. Broad-scale assessments of vegetation responses to drought are needed to anticipate, manage, and potentially mitigate climate-change effects on ecosystems. We quantified the drought sensitivity of vegetation in the Pacific Northwest, USA, as the percent reduction in vegetation greenness under droughts relative to baseline moisture conditions. At a regional scale, shrub-steppe ecosystems—with drier climates and lower biomass—showed greater drought sensitivity than conifer forests. However, variability in drought sensitivity was considerable within biomes and within ecosystems and was mediated by landscape topography, climate, and soil characteristics. Drought sensitivity was generally greater in areas with higher elevation, drier climate, and greater soil bulk density. Ecosystems with high drought sensitivity included dry forests along ecotones to shrublands, Rocky Mountain subalpine forests, and cold upland sagebrush communities. In forests, valley bottoms and areas with low soil bulk density and high soil available water capacity showed reduced drought sensitivity, suggesting their potential as drought refugia. These regional-scale drought-sensitivity patterns discerned from remote sensing can complement plot-scale studies of plant physiological responses to drought to help inform climate-adaptation planning as drought conditions intensify.
","language":"English","publisher":"Springer Nature","doi":"10.1038/s41598-020-75273-5","usgsCitation":"Cartwright, J.M., Littlefield, C.E., Michalak, J., Lawler, J.J., and Dobrowski, S., 2020, Topographic, soil, and climate drivers of drought sensitivity in forests and shrublands of the Pacific Northwest, USA: Scientific Reports, v. 10, 18486, 13 p., https://doi.org/10.1038/s41598-020-75273-5.","productDescription":"18486, 13 p.","ipdsId":"IP-105631","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":454954,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-020-75273-5","text":"Publisher Index Page"},{"id":436741,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9UNYG2R","text":"USGS data release","linkHelpText":"Analysis of drought sensitivity in the Pacific Northwest (Washington, Oregon, and Idaho) from 2000 through 2016"},{"id":436740,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9UNYG2R","text":"USGS data release","linkHelpText":"Analysis of drought sensitivity in the Pacific Northwest (Washington, Oregon, and Idaho) from 2000 through 2016"},{"id":380119,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington, Oregon, Idaho","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.62890625,\n 48.45835188280866\n ],\n [\n -124.76074218749999,\n 41.86956082699455\n ],\n [\n -110.91796875,\n 41.83682786072714\n ],\n [\n -111.09374999999999,\n 45.089035564831036\n ],\n [\n -113.37890625,\n 44.87144275016589\n ],\n [\n -116.27929687499999,\n 49.06666839558117\n ],\n [\n -123.3984375,\n 49.009050809382046\n ],\n [\n -124.62890625,\n 48.45835188280866\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"10","noUsgsAuthors":false,"publicationDate":"2020-10-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Cartwright, Jennifer M. 0000-0003-0851-8456 jmcart@usgs.gov","orcid":"https://orcid.org/0000-0003-0851-8456","contributorId":5386,"corporation":false,"usgs":true,"family":"Cartwright","given":"Jennifer","email":"jmcart@usgs.gov","middleInitial":"M.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":581,"text":"Tennessee Water Science Center","active":true,"usgs":true}],"preferred":true,"id":803898,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Littlefield, Caitlin E. 0000-0003-3771-7956","orcid":"https://orcid.org/0000-0003-3771-7956","contributorId":220623,"corporation":false,"usgs":false,"family":"Littlefield","given":"Caitlin","email":"","middleInitial":"E.","affiliations":[{"id":36523,"text":"University of Montana","active":true,"usgs":false}],"preferred":false,"id":803899,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Michalak, Julia 0000-0002-2524-8390","orcid":"https://orcid.org/0000-0002-2524-8390","contributorId":210589,"corporation":false,"usgs":false,"family":"Michalak","given":"Julia","email":"","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":803900,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lawler, Joshua J.","contributorId":73327,"corporation":false,"usgs":false,"family":"Lawler","given":"Joshua","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":803901,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dobrowski, Solomon","contributorId":229621,"corporation":false,"usgs":false,"family":"Dobrowski","given":"Solomon","affiliations":[{"id":36523,"text":"University of Montana","active":true,"usgs":false}],"preferred":false,"id":803902,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70217193,"text":"70217193 - 2020 - Restoration of rapids habitat in a Great Lakes connecting channel, the St. Marys River, Michigan","interactions":[],"lastModifiedDate":"2021-01-12T13:21:25.45235","indexId":"70217193","displayToPublicDate":"2020-10-28T07:19:31","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3271,"text":"Restoration Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Restoration of rapids habitat in a Great Lakes connecting channel, the St. Marys River, Michigan","docAbstract":"Aquatic habitat has been extensively altered throughout the Laurentian Great Lakes to increase navigation connectivity. In particular, the St. Marys River, a Great Lakes connecting channel, lost >50% of its historic rapids habitat over the past century. In 2016, the natural flow was restored to the Little Rapids area of the St. Marys River. The goal of our study was to evaluate physical and ecological responses to the restoration of the Little Rapids area. Extensive habitat and biological data were collected prior to restoration (2013 and 2014), and after restoration (2017 and 2018). Measured parameters included total suspended solids, current velocity, benthic macroinvertebrates, and larval, juvenile, and adult fishes. Total suspended solids stayed low (<4 mg/L) following restoration, with the exception of a single construction‐related event. Pre‐restoration data indicated that all measured velocities were below the target flow rate of 0.24 m/s, whereas 70% of the measured habitat was above the target flow post‐restoration. Abundance and richness of benthic macroinvertebrates were reduced following restoration (>90% reduction). We observed a 45% increase in richness of larval fish 2 years after restoration and a 131% increase in catch per unit effort. For adult fishes, the proportion of individuals with a preference for fast‐moving waters increased from 1.5 to 45% in the restored area, and from 7 to 15% upstream of the restored area; a similar response was observed for lithophilic spawners. The physical and biological conditions of the Little Rapids improved and resembled conditions typical of rapids habitat extent in other areas of the river and other systems.
Cover crops are planted during the off-season to protect the soil and improve watershed management. The ability to map cover crop termination dates over agricultural landscapes is essential for quantifying conservation practice implementation, and enabling estimation of biomass accumulation during the active cover period. Remote sensing detection of end-of-season (termination) for cover crops has been limited by the lack of high spatial and temporal resolution observations and methods. In this paper, a new within-season termination (WIST) algorithm was developed to map cover crop termination dates using the Vegetation and Environment monitoring New Micro Satellite (VENµS) imagery (5 m, 2 days revisit). The WIST algorithm first detects the downward trend (senescent period) in the Normalized Difference Vegetation Index (NDVI) time-series and then refines the estimate to the two dates with the most rapid rate of decrease in NDVI during the senescent period. The WIST algorithm was assessed using farm operation records for experimental fields at the Beltsville Agricultural Research Center (BARC). The crop termination dates extracted from VENµS and Sentinel-2 time-series in 2019 and 2020 were compared to the recorded termination operation dates. The results show that the termination dates detected from the VENµS time-series (aggregated to 10 m) agree with the recorded harvest dates with a mean absolute difference of 2 days and uncertainty of 4 days. The operational Sentinel-2 time-series (10 m, 4–5 days revisit) also detected termination dates at BARC but had 7% missing and 10% false detections due to less frequent temporal observations. Near-real-time simulation using the VENµS time-series shows that the average lag times of termination detection are about 4 days for VENµS and 8 days for Sentinel-2, not including satellite data latency. The study demonstrates the potential for operational mapping of cover crop termination using high temporal and spatial resolution remote sensing data.
","language":"English","publisher":"MDPI","doi":"10.3390/rs12213524","usgsCitation":"Gao, F., Anderson, M., and Hively, W.D., 2020, Detecting cover crop end-of-season using VENµS and sentinel-2 satellite imagery: Remote Sensing, v. 12, no. 21, 22 p., https://doi.org/10.3390/rs12213524.","productDescription":"22 p.","ipdsId":"IP-123386","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":454959,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs12213524","text":"Publisher Index Page"},{"id":380903,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"12","issue":"21","noUsgsAuthors":false,"publicationDate":"2020-10-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Gao, Feng 0000-0002-1865-2846","orcid":"https://orcid.org/0000-0002-1865-2846","contributorId":70671,"corporation":false,"usgs":false,"family":"Gao","given":"Feng","email":"","affiliations":[{"id":6622,"text":"US Department of Agriculture","active":true,"usgs":false}],"preferred":false,"id":805911,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Anderson, Martha","contributorId":210925,"corporation":false,"usgs":false,"family":"Anderson","given":"Martha","affiliations":[],"preferred":false,"id":805912,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hively, W. Dean 0000-0002-5383-8064","orcid":"https://orcid.org/0000-0002-5383-8064","contributorId":201565,"corporation":false,"usgs":true,"family":"Hively","given":"W.","email":"","middleInitial":"Dean","affiliations":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":805913,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70216661,"text":"70216661 - 2020 - Virome of bat guano from nine northern California roosts","interactions":[],"lastModifiedDate":"2021-02-04T00:06:57.522623","indexId":"70216661","displayToPublicDate":"2020-10-28T07:05:46","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2497,"text":"Journal of Virology","active":true,"publicationSubtype":{"id":10}},"title":"Virome of bat guano from nine northern California roosts","docAbstract":"Bats are hosts to a large variety of viruses, including many capable of cross species transmissions to other mammals or humans. We characterized the virome in guano from five common bat species in 9 Northern California roosts and a pool of 5 individual bats. Genomes belonging to 14 viral families known to infect mammals and 17 viral families infecting insects or of unknown tropism were detected. Near or complete genomes of a novel parvovirus, astrovirus, nodavirus, CRESS-DNA viruses and densoviruses and more partial genomes of a novel alphacoronavirus, and bunyavirus were characterized. Lower numbers of reads with >90% amino acid identity to previously described calicivirus, circovirus, adenoviruses, hepatovirus, bocaparvoviruses, and polyomavirus in other bat species were also found likely reflecting their wide distribution among different bats. Unexpectedly a few sequence reads of canine parvovirus 2 and the recently described mouse kidney parvovirus were also detected and their presence confirmed by PCR possibly originating from guano contamination by carnivores and rodents. The majority of eukaryotic viral reads were highly divergent indicating that numerous viruses still remain to be characterized even from such a heavily investigated order as Chiroptera.
","language":"English","publisher":"American Society for Microbiology","doi":"10.1128/JVI.01713-20","usgsCitation":"Li, Y., Altan, E., Reyes, G., Halstead, B., Deng, X., and Delwart, E., 2020, Virome of bat guano from nine northern California roosts: Journal of Virology, v. 95, no. 3, p. e01713-e01720, https://doi.org/10.1128/JVI.01713-20.","productDescription":"8 p.","startPage":"e01713","endPage":"e01720","ipdsId":"IP-122602","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":454960,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/7925108","text":"External Repository"},{"id":380833,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Northern California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.25537109375,\n 37.47485808497102\n ],\n [\n -119.72900390625001,\n 37.47485808497102\n ],\n [\n -119.72900390625001,\n 41.96765920367816\n ],\n [\n -124.25537109375,\n 41.96765920367816\n ],\n [\n -124.25537109375,\n 37.47485808497102\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"95","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Li, Yanpeng","contributorId":245294,"corporation":false,"usgs":false,"family":"Li","given":"Yanpeng","email":"","affiliations":[{"id":49143,"text":"Vitalant Research Institute, San Francisco, California, USA","active":true,"usgs":false}],"preferred":false,"id":805783,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Altan, Eda","contributorId":245295,"corporation":false,"usgs":false,"family":"Altan","given":"Eda","email":"","affiliations":[{"id":49143,"text":"Vitalant Research Institute, San Francisco, California, USA","active":true,"usgs":false}],"preferred":false,"id":805784,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Reyes, Gabriel 0000-0001-9281-5300 greyes@usgs.gov","orcid":"https://orcid.org/0000-0001-9281-5300","contributorId":199338,"corporation":false,"usgs":true,"family":"Reyes","given":"Gabriel","email":"greyes@usgs.gov","affiliations":[],"preferred":true,"id":805785,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Halstead, Brian J. 0000-0002-5535-6528 bhalstead@usgs.gov","orcid":"https://orcid.org/0000-0002-5535-6528","contributorId":3051,"corporation":false,"usgs":true,"family":"Halstead","given":"Brian J.","email":"bhalstead@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":805786,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Deng, Xutao","contributorId":245296,"corporation":false,"usgs":false,"family":"Deng","given":"Xutao","email":"","affiliations":[{"id":49143,"text":"Vitalant Research Institute, San Francisco, California, USA","active":true,"usgs":false}],"preferred":false,"id":805787,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Delwart, Eric","contributorId":179329,"corporation":false,"usgs":false,"family":"Delwart","given":"Eric","email":"","affiliations":[],"preferred":false,"id":805788,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70267767,"text":"70267767 - 2020 - Ontogenetic shifts in mesohabitat use of young-of-year Rio Grande blue sucker in the Big Bend region of the Rio Grande","interactions":[],"lastModifiedDate":"2025-05-30T16:03:05.271414","indexId":"70267767","displayToPublicDate":"2020-10-28T00:00:00","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1528,"text":"Environmental Biology of Fishes","active":true,"publicationSubtype":{"id":10}},"title":"Ontogenetic shifts in mesohabitat use of young-of-year Rio Grande blue sucker in the Big Bend region of the Rio Grande","docAbstract":"Alteration of flow regimes by anthropogenic activities is one of the primary environmental problems in riverine systems. Understanding how hydrologic conditions can affect ontogenetic habitat shifts of imperiled fishes is important in order to develop conservation and management strategies for each life-history stage. We examined relationships between the abundance of young-of-the-year (YOY) Rio Grande Blue Sucker and various abiotic variables in the Trans-Pecos region of the Rio Grande in Texas, USA. We used open N-mixture modeling to better understand the factors affecting ontogenetic habitat shifts of the imperiled aridland river fish. In addition, we examined differences in Rio Grande Blue Sucker total length among three mesohabitat types (pool, riffle, and run). The results of open N-mixture modeling suggested that as pool area increased, the abundance of YOY Rio Grande Blue Sucker increased. Total length of YOY Rio Grande Blue Sucker also significantly differed among the three mesohabitat types. The total lengths of YOY Rio Grande Blue Sucker in pool habitats were lower than in other mesohabitats, suggesting that YOY Rio Grande Blue Sucker undergo ontogenetic habitat shifts into greater current velocity habitats as they grow. The habitat associations we documented support the growing body of research emphasizing the importance of maintaining sufficient and appropriately timed flows to avoid prolonged low flows that limit habitat availability for native fish species during sensitive life stages in the Rio Grande and other aridland rivers.
","language":"English","publisher":"Springer Nature","doi":"10.1007/s10641-020-01038-8","usgsCitation":"Miyazono, S., Pease, A., Fritts, S., and Grabowski, T.B., 2020, Ontogenetic shifts in mesohabitat use of young-of-year Rio Grande blue sucker in the Big Bend region of the Rio Grande: Environmental Biology of Fishes, v. 103, p. 1471-1480, https://doi.org/10.1007/s10641-020-01038-8.","productDescription":"10 p.","startPage":"1471","endPage":"1480","ipdsId":"IP-118286","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":489286,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Texas","otherGeospatial":"Rio Grande in the Big Bend region","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -103.91886105019951,\n 29.728911907450694\n ],\n [\n -103.91886105019951,\n 28.965625411076672\n ],\n [\n -102.76942901752302,\n 28.965625411076672\n ],\n [\n -102.76942901752302,\n 29.728911907450694\n ],\n [\n -103.91886105019951,\n 29.728911907450694\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"103","noUsgsAuthors":false,"publicationDate":"2020-10-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Miyazono, Seiji","contributorId":356122,"corporation":false,"usgs":false,"family":"Miyazono","given":"Seiji","affiliations":[{"id":37463,"text":"TTU","active":true,"usgs":false}],"preferred":false,"id":938781,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pease, Allison A.","contributorId":356124,"corporation":false,"usgs":false,"family":"Pease","given":"Allison A.","affiliations":[{"id":37463,"text":"TTU","active":true,"usgs":false}],"preferred":false,"id":938782,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fritts, Sarah","contributorId":356126,"corporation":false,"usgs":false,"family":"Fritts","given":"Sarah","affiliations":[{"id":84915,"text":"tsu","active":true,"usgs":false}],"preferred":false,"id":938783,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Grabowski, Timothy B. 0000-0001-9763-8948 tgrabowski@usgs.gov","orcid":"https://orcid.org/0000-0001-9763-8948","contributorId":4178,"corporation":false,"usgs":true,"family":"Grabowski","given":"Timothy","email":"tgrabowski@usgs.gov","middleInitial":"B.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":938780,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70217538,"text":"70217538 - 2020 - Cenozoic tectonic evolution of the Ecemiş fault zone and adjacent basins, central Anatolia, Turkey during the transition from Arabia - Eurasia collision to escape tectonics","interactions":[],"lastModifiedDate":"2021-01-21T21:34:51.473223","indexId":"70217538","displayToPublicDate":"2020-10-27T15:31:00","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1820,"text":"Geosphere","active":true,"publicationSubtype":{"id":10}},"title":"Cenozoic tectonic evolution of the Ecemiş fault zone and adjacent basins, central Anatolia, Turkey during the transition from Arabia - Eurasia collision to escape tectonics","docAbstract":"The effects of Arabia-Eurasia collision are recorded in faults, basins, and exhumed metamorphic massifs across eastern and central Anatolia. These faults and basins also preserve evidence of major changes in deformation and associated sedimentary processes along major suture zones including the Inner Tauride suture where it lies along the southern (Ecemiş) segment of the Central Anatolian fault zone. Stratigraphic and structural data from the Ecemiş fault zone, adjacent NE Ulukışla basin, and metamorphic dome (Niğde Massif) record two fundamentally different stages in the Cenozoic tectonic evolution of this part of central Anatolia. The Paleogene sedimentary and volcanic strata of the NE Ulukışla basin (Ecemiş corridor) were deposited in marginal marine to marine environments on the exhuming Niğde Massif and east of it. A late Eocene–Oligocene transpressional stage of deformation involved oblique northward thrusting of older Paleogene strata onto the eastern Niğde Massif and of the eastern massif onto the rest of the massif, reburying the entire massif to >10 km depth and accompanied by left-lateral motion on the Ecemiş fault zone. A profound change in the tectonic setting at the end of the Oligocene produced widespread transtensional deformation across the area west of the Ecemiş fault zone in the Miocene. In this stage, the Ecemiş fault zone had at least 25 km of left-lateral offset. Before and during this faulting episode, the central Tauride Mountains to the east became a source of sediments that were deposited in small Miocene transtensional basins formed on the Eocene–Oligocene thrust belt between the Ecemiş fault zone and the Niğde Massif. Normal faults compatible with SW-directed extension cut across the Niğde Massif and are associated with a second (Miocene) re-exhumation of the Massif. Geochronology and thermochronology indicate that the transtensional stage started at ca. 23–22 Ma, coeval with large and diverse geological and tectonic changes across Anatolia.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/GES02255.1","usgsCitation":"Umhoefer, P.J., Thompson, S., Lefebre, C., Cosca, M., Teyssier, C., and Whitney, D.L., 2020, Cenozoic tectonic evolution of the Ecemiş fault zone and adjacent basins, central Anatolia, Turkey during the transition from Arabia - Eurasia collision to escape tectonics: Geosphere, v. 16, no. 6, p. 1358-1384, https://doi.org/10.1130/GES02255.1.","productDescription":"27 p.","startPage":"1358","endPage":"1384","ipdsId":"IP-120164","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":454961,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/ges02255.1","text":"Publisher Index Page"},{"id":382449,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Turkey","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 31.420898437499996,\n 36.932330061503144\n ],\n [\n 36.309814453125,\n 36.932330061503144\n ],\n [\n 36.309814453125,\n 39.93501296038254\n ],\n [\n 31.420898437499996,\n 39.93501296038254\n ],\n [\n 31.420898437499996,\n 36.932330061503144\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"16","issue":"6","noUsgsAuthors":false,"publicationDate":"2020-10-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Umhoefer, Paul J.","contributorId":200335,"corporation":false,"usgs":false,"family":"Umhoefer","given":"Paul","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":808611,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thompson, Stuart","contributorId":248207,"corporation":false,"usgs":false,"family":"Thompson","given":"Stuart","email":"","affiliations":[{"id":27205,"text":"U. Arizona","active":true,"usgs":false}],"preferred":false,"id":808612,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lefebre, Come","contributorId":248208,"corporation":false,"usgs":false,"family":"Lefebre","given":"Come","email":"","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":808613,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cosca, Michael 0000-0002-0600-7663","orcid":"https://orcid.org/0000-0002-0600-7663","contributorId":33043,"corporation":false,"usgs":true,"family":"Cosca","given":"Michael","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":808614,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Teyssier, Christian","contributorId":248209,"corporation":false,"usgs":false,"family":"Teyssier","given":"Christian","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":808615,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Whitney, Donna L.","contributorId":187715,"corporation":false,"usgs":false,"family":"Whitney","given":"Donna","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":808616,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70201829,"text":"tm4A3 - 2020 - Statistical methods in water resources","interactions":[{"subject":{"id":47512,"text":"twri04A3 - 2002 - Statistical methods in water resources","indexId":"twri04A3","publicationYear":"2002","noYear":false,"displayTitle":"Statistical Methods in Water Resources","title":"Statistical methods in water resources"},"predicate":"SUPERSEDED_BY","object":{"id":70201829,"text":"tm4A3 - 2020 - Statistical methods in water resources","indexId":"tm4A3","publicationYear":"2020","noYear":false,"title":"Statistical methods in water resources"},"id":1}],"lastModifiedDate":"2024-08-13T14:02:36.434133","indexId":"tm4A3","displayToPublicDate":"2020-10-27T09:00:00","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":335,"text":"Techniques and Methods","code":"TM","onlineIssn":"2328-7055","printIssn":"2328-7047","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"4-A3","displayTitle":"Statistical Methods in Water Resources","title":"Statistical methods in water resources","docAbstract":"This text began as a collection of class notes for a course on applied statistical methods for hydrologists taught at the U.S. Geological Survey (USGS) National Training Center. Course material was formalized and organized into a textbook, first published in 1992 by Elsevier as part of their Studies in Environmental Science series. In 2002, the work was made available online as a USGS report.
The text has now been updated as a USGS Techniques and Methods Report. It is intended to be a text in applied statistics for hydrology, environmental science, environmental engineering, geology, or biology that addresses distinctive features of environmental data. For example, water resources data tend to have many variables with a lower bound of zero, tend to be more skewed than data from many other disciplines, commonly contain censored data (less than values), and assumptions that the data are normally distributed are not appropriate. Computer-intensive methods (bootstrapping and permutation tests) now improve upon and replace the dependence on t-intervals, t-tests, and analysis of variance. A new chapter on sampling design addresses questions such as “How many observations do I need?” The chapter also presents distribution-free methods to help plan sampling efforts. The trends chapter has been updated to include the WRTDS (Weighted Regressions on Time, Discharge, and Season) method for analysis of water-quality data. This new version contains updated graphics and updated guidance on the use of statistical techniques. The text utilizes R, a programming language and open-source software environment, for all exercises and most graphics, and the R code used to generate figures and examples is provided for download.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm4A3","usgsCitation":"Helsel, D.R., Hirsch, R.M., Ryberg, K.R., Archfield, S.A., and Gilroy, E.J., 2020, Statistical methods in water resources: U.S. Geological Survey Techniques and Methods, book 4, chap. A3, 458 p., https://doi.org/10.3133/tm4a3. [Supersedes USGS Techniques of Water-Resources Investigations, book 4, chap. A3, version 1.1.]","productDescription":"Report: xxii, 458 p.; Data Release","numberOfPages":"484","onlineOnly":"N","additionalOnlineFiles":"Y","ipdsId":"IP-089727","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":418371,"rank":5,"type":{"id":12,"text":"Errata"},"url":"https://pubs.usgs.gov/tm/04/a03/Errata_Sheet.pdf","text":"Errata Sheet","size":"136 KB","linkFileType":{"id":1,"text":"pdf"},"description":"Errata Sheet"},{"id":379731,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://store.usgs.gov/product/533012","text":"Print Version Available"},{"id":374999,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9JWL6XR","text":"USGS data release","linkHelpText":"Statistical Methods in Water Resources - Supporting Materials"},{"id":375013,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/04/a03/tm4a3.pdf","text":"Report","size":"9.26 MB","linkFileType":{"id":1,"text":"pdf"},"description":"TM 4-A3"},{"id":375000,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/tm/04/a03/coverthb.jpg"}],"publicComments":"Techniques and Methods 4-A3 supersedes Techniques of Water-Resources Investigations, book 4, chapter A3, version 1.1.","contact":"Chief, Analysis and Prediction Branch
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This report provides an overview of existing hydrologic information describing the quality, quantity, and extent of the major surface-water and groundwater resources in the Cheyenne and Arapaho Tribal jurisdictional area, west-central Oklahoma. Hydrologic information is provided for five major river systems (Cimarron River, North Canadian River, Canadian River, Washita River, and North Fork Red River), two reservoirs (Foss Reservoir and Canton Lake), and eight aquifers consisting of the alluvial aquifers associated with each of the five major river systems and three major bedrock aquifers (Ogallala aquifer, Elk City aquifer, and Rush Springs aquifer).
Types of information provided about rivers and reservoirs for the Cheyenne and Arapaho Tribal jurisdictional area include diversion sites and amounts of water allocated and diverted for permitted uses in 2015; treated wastewater discharge sites and amounts discharged in 2015; and characteristics describing water-quality field properties, major ions, nutrients, and selected trace elements. Major ions, nutrients, and selected trace elements are compared to secondary maximum contaminant levels and maximum contaminant levels for finished drinking water. Additionally, statistics are provided describing daily, monthly, and annual streamflow characteristics at 12 U.S. Geological Survey streamgages. Streamflow statistics include the magnitudes and frequencies of floods, base-flow characteristics, and long-term streamflow trends.
Types of information provided about the aquifers include amounts of water allocated and pumped for permitted uses in 2015; characteristics of groundwater describing water-quality field properties, major ions, nitrate (measured as nitrogen), and selected trace elements with comparisons to secondary maximum contaminant levels and maximum contaminant levels for finished drinking water; groundwater levels and long-term changes in water levels; and ranges of hydraulic conductivity, aquifer recharge, specific yield, transmissivity, and well yields from reports and groundwater-flow models.
Surface water is used primarily for irrigation and mining and other nonconsumptive uses in the Cheyenne and Arapaho Tribal jurisdictional area, except from the Washita and North Fork Red Rivers, where water is treated for use as a public-water supply. Large concentrations of dissolved solids are the primary limiting factor affecting the use of surface water. Median concentrations of dissolved solids in surface water range from less than 1,000 milligrams per liter (mg/L) in samples from the North Canadian River to greater than 9,000 mg/L in samples from the Cimarron River. Large dissolved solids concentrations are correlated with hard water. Median hardness as calcium carbonate concentrations in surface water ranges from 427 mg/L in samples from Canton Lake to 1,000 mg/L in samples from the Washita River.
In 2015, groundwater was used at more than twice the rate of surface water in the Cheyenne and Arapaho Tribal jurisdictional area. Although the alluvial aquifers are considered reliably good sources of water in the Cheyenne and Arapaho Tribal jurisdictional area, concentrations of nitrate (measured as nitrogen) exceed the maximum contaminant level of 10 mg/L established by the U.S. Environmental Protection Agency for finished drinking water in parts of all of the alluvial aquifers. Water from the three major bedrock aquifers is used for irrigation, mining, public-water supply, and other uses; however, large concentrations of dissolved solids, nitrate (measured as nitrogen), and naturally occurring trace elements such as arsenic and uranium may limit the use of groundwater as a source of public-water supply in some areas. As of 2015, the depletion of groundwater from the major aquifers in west-central Oklahoma is a minor concern to the Oklahoma Water Resources Board. Groundwater levels and other hydrologic information show that recharge rates exceed the rates of water pumped from aquifers, except in areas that may be affected locally by groundwater depletions.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205105","collaboration":"Prepared in cooperation with the Cheyenne and Arapaho Tribes of Oklahoma and the Bureau of Indian Affairs","usgsCitation":"Becker, C.J., and Varonka, M.S., 2020, Water resources in the Cheyenne and Arapaho Tribal jurisdictional area, west-central Oklahoma, with an analysis of data gaps through 2015 (ver. 1.1, January 2021): U.S. Geological Survey Scientific Investigations Report 2020–5105, 158 p., 1 app., https://doi.org/10.3133/sir20205105..","productDescription":"xi, 158 p.","numberOfPages":"175","onlineOnly":"Y","ipdsId":"IP-109610","costCenters":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":382059,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2020/5105/versionHist.txt","text":"Version History","size":"4.0 kB","linkFileType":{"id":2,"text":"txt"},"description":"SIR 2020–5105 Version History"},{"id":379749,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5105/sir20205105.pdf","text":"Report","size":"36.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020–5105"},{"id":379748,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5105/coverthb2.jpg"}],"country":"United States","state":"Oklahoma","otherGeospatial":"Cheyenne and Arapaho Tribal Jurisdictional Area","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-99.3595,35.1163],[-99.4067,35.1161],[-99.409,35.1148],[-99.4129,35.1134],[-99.4163,35.1134],[-99.4196,35.1143],[-99.4219,35.1138],[-99.4258,35.1129],[-99.4281,35.1111],[-99.4337,35.1097],[-99.4393,35.111],[-99.4432,35.1124],[-99.4449,35.116],[-99.7833,35.1161],[-99.7839,35.1151],[-99.7852,35.028],[-99.8897,35.0277],[-100.0008,35.0295],[-100.0014,35.1818],[-100.0015,35.2034],[-100.0013,35.2689],[-100.0012,35.293],[-100.0009,35.4223],[-100.0014,35.4558],[-100.0011,35.6197],[-100.001,35.64],[-100.0015,35.8008],[-100.0015,35.8782],[-100.0015,35.9478],[-100.002,36.0539],[-100.0025,36.1891],[-100.003,36.3134],[-100.0031,36.3348],[-100.0038,36.4998],[-100.0044,36.5849],[-100.0045,36.5917],[-99.6193,36.5916],[-99.605,36.5917],[-99.6043,36.506],[-99.6038,36.3051],[-99.6034,36.2457],[-99.5954,36.2457],[-99.5976,36.1639],[-99.382,36.1645],[-98.9565,36.1587],[-98.7878,36.1613],[-98.7428,36.1625],[-98.7251,36.1634],[-98.6362,36.1636],[-98.634,36.1636],[-98.3177,36.1645],[-98.2122,36.1656],[-98.1057,36.1658],[-97.6759,36.1663],[-97.6765,36.0715],[-97.6763,35.984],[-97.6761,35.8973],[-97.6757,35.7253],[-97.6753,35.5506],[-97.6719,35.5506],[-97.6729,35.4639],[-97.6733,35.3763],[-97.6729,35.335],[-97.6836,35.3351],[-97.6898,35.3338],[-97.6948,35.3339],[-97.7016,35.3353],[-97.7033,35.3353],[-97.7073,35.334],[-97.7118,35.3313],[-97.7181,35.3287],[-97.7231,35.3278],[-97.7288,35.3274],[-97.7367,35.328],[-97.7423,35.3298],[-97.749,35.3326],[-97.7546,35.3354],[-97.7635,35.3414],[-97.7759,35.3434],[-97.7917,35.3408],[-97.829,35.3348],[-97.838,35.3354],[-97.8464,35.3368],[-97.8565,35.341],[-97.8582,35.3428],[-97.8614,35.3551],[-97.8636,35.3588],[-97.8669,35.3615],[-97.8703,35.3629],[-97.8754,35.3625],[-97.8811,35.3608],[-97.8845,35.3572],[-97.8885,35.3545],[-97.8936,35.3513],[-97.9009,35.3514],[-97.9082,35.3528],[-97.9105,35.3533],[-97.915,35.3556],[-97.925,35.3612],[-97.9351,35.3649],[-97.9368,35.3672],[-97.9378,35.3744],[-97.9395,35.3763],[-97.9429,35.3772],[-97.9474,35.3777],[-97.9491,35.3764],[-97.9502,35.3745],[-97.9492,35.3668],[-97.951,35.3596],[-97.9527,35.3555],[-97.955,35.3528],[-97.9562,35.3519],[-97.9663,35.3525],[-97.9697,35.3529],[-97.9736,35.3543],[-97.9843,35.3599],[-97.9994,35.365],[-98.0184,35.3765],[-98.0985,35.3767],[-98.305,35.3744],[-98.3051,35.5437],[-98.3085,35.541],[-98.3119,35.5401],[-98.3142,35.5406],[-98.3193,35.5429],[-98.3193,35.5438],[-98.3187,35.5479],[-98.3181,35.5502],[-98.6199,35.552],[-98.6209,35.4639],[-98.6216,35.2038],[-98.616,35.2038],[-98.6177,35.0994],[-98.621,35.0981],[-98.6255,35.1035],[-98.6294,35.1167],[-98.6355,35.1231],[-98.6406,35.1231],[-98.6429,35.1145],[-98.6451,35.1113],[-98.6496,35.1141],[-98.6513,35.1177],[-98.649,35.1195],[-98.6485,35.1213],[-98.6485,35.1231],[-98.6513,35.125],[-98.6575,35.1236],[-98.6665,35.1209],[-98.6738,35.1187],[-98.6778,35.1082],[-98.6822,35.1101],[-98.6856,35.1078],[-98.6985,35.1115],[-98.7042,35.111],[-98.7109,35.1065],[-98.7132,35.1065],[-98.721,35.1138],[-98.7255,35.1115],[-98.7317,35.1129],[-98.7351,35.1029],[-98.7379,35.102],[-98.7401,35.107],[-98.748,35.1166],[-98.8244,35.1176],[-98.9312,35.1168],[-98.9807,35.1173],[-99.0425,35.1168],[-99.2555,35.1161],[-99.3595,35.1163]]]},\"properties\":{\"name\":\"Beckham\",\"state\":\"OK\"}}]}","edition":"Version 1.0: October 27, 2020; Version 1.1: January 11, 2021","contact":"Director, Oklahoma-Texas Water Science Center
U.S. Geological Survey
1505 Ferguson Lane
Austin, TX 78754–4501
Director, Western Ecological Research Center
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3020 State University Drive East
Sacramento, California 95819
The utilization, preservation, and conservation of the Nation’s resources requires well-informed management decisions. The North Atlantic and Appalachian Region (NAAR) of the U.S. Geological Survey (USGS) supports science-based decision making for Federal, State, and local policymakers to meet the challenges of today and into the future. The science centers in the NAAR have well-deserved reputations as world leaders in delivering unbiased science. We help protect the lives and property of our families, friends, neighbors, and the Nation by providing the data and scientific interpretation that decision makers need to make informed choices on a myriad of topics. Many of our jobs include inherent risk. When others are moving themselves and their families to higher ground during storms, NAAR employees can be found heading toward high water to ensure that accurate streamflow and storm-tide data continue to be collected and delivered to the public and first responders.
In March 2020, the world changed, and the NAAR staff adapted to it. Despite the challenges, the NAAR has had an incredibly productive year. I am not just citing publications (with our labs and field offices closed in the spring, centers increased annual publications by 10 to 40 percent compared with 2019) or partnerships (new science initiatives and partnerships are up significantly as well). Leaders at the center level created the right environments for their teams to be safe but still meet and exceed their program goals. Our vast data collection networks were maintained and enhanced. Our laboratories met holding times and quality-control objectives. When folks asked for help, our staff provided. Some solutions were not perfect at first, but they just kept trying. What started as a short-term inconvenience may now have become the new normal, but in quickly adapting, the NAAR staff showed dedication and wisdom, made the region a little safer, and just might change the world. This general information product highlights just a few of the many accomplishments of the NAAR staff during these challenging times and offers a taste of all the great work being done by the USGS community.
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