{"pageNumber":"254","pageRowStart":"6325","pageSize":"25","recordCount":68827,"records":[{"id":70208763,"text":"70208763 - 2020 - Increased prespawning mortality threatens an integrated natural- and hatchery-origin sockeye salmon population in the Lake Washington Basin","interactions":[],"lastModifiedDate":"2020-03-02T06:23:12","indexId":"70208763","displayToPublicDate":"2020-02-27T06:44:44","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1661,"text":"Fisheries Research","active":true,"publicationSubtype":{"id":10}},"title":"Increased prespawning mortality threatens an integrated natural- and hatchery-origin sockeye salmon population in the Lake Washington Basin","docAbstract":"The life cycle of diadromous fishes such as salmonids involves natural mortality in a series of distinct life history stages, occurring sequentially in different habitats. Decades of research have emphasized mortality at the embryo, juvenile, and sub-adult stages but it is increasingly clear that some adults that survive and return to freshwater habitats die during the final homeward migration or after they reach the spawning grounds, prior to breeding. These are termed “en route” and “prespawning” mortality, respectively, and can threaten populations depleted by mortality at previous stages. In this study, we present evidence that the sockeye salmon, Oncorhynchus nerka, population that returns to the Lake Washington Basin, in Washington State, USA, is experiencing both forms of adult mortality. Counts of the salmon entering the basin on their return migration in June and July were compared to counts in the major spawning grounds in September through November for 1995–2018. The disparity has increased markedly in recent years. The counts on the spawning grounds have decreased as a proportion of the number entering the system with an average 49 % of sockeye unaccounted for, consistent with increased en route mortality. In addition, prespawning mortality rates have increased in salmon that reach the Cedar River, the main spawning tributary, both at a hatchery holding adult fish in 1995–2018, and in the naturally spawning populations when monitored in the last five years. Hatchery records indicated <10 % prespawning mortality for 1995–2010, increasing to an average 43 % for 2014 – 2018. Recent carcass surveys in the Cedar River documented that 33.6% (2014), 22.3% (2015), 30.3% (2016) and 50.0% (2018) of female sockeye died before completing spawning. These recent increases in prespawning mortality have been associated with warm water during entry to freshwater, but comparably warm water in past decades had no such effect. Steady warming of river temperatures around the median run completion date from < 8.0 °C to > 13.0 °C was correlated with increased prespawning mortality rates at the hatchery from 1995–2018. We conclude that warming conditions during migration and spawning, in concert with other factors such as infections with pathogens, are responsible for the increased prespawning mortality of adult sockeye salmon that are high enough to threaten the population’s viability.","language":"English","publisher":"Elsevier","doi":"10.1016/j.fishres.2020.105527","usgsCitation":"Barnett, H.K., Quinn, T.P., Bhuthimethee, M., and Winton, J., 2020, Increased prespawning mortality threatens an integrated natural- and hatchery-origin sockeye salmon population in the Lake Washington Basin: Fisheries Research, v. 227, 105527, 10 p., https://doi.org/10.1016/j.fishres.2020.105527.","productDescription":"105527, 10 p.","ipdsId":"IP-115029","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":372723,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Lake Washington Basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -122.29980468749999,\n              47.49772004565105\n            ],\n            [\n              -122.18238830566406,\n              47.49772004565105\n            ],\n            [\n              -122.18238830566406,\n              47.758714187846294\n            ],\n            [\n              -122.29980468749999,\n              47.758714187846294\n            ],\n            [\n              -122.29980468749999,\n              47.49772004565105\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"227","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Barnett, Heidy K","contributorId":222835,"corporation":false,"usgs":false,"family":"Barnett","given":"Heidy","email":"","middleInitial":"K","affiliations":[{"id":40608,"text":"West Fork Environmental, Tumwater, WA","active":true,"usgs":false}],"preferred":false,"id":783313,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Quinn, Thomas P.","contributorId":167272,"corporation":false,"usgs":false,"family":"Quinn","given":"Thomas","email":"","middleInitial":"P.","affiliations":[{"id":24671,"text":"School of Aquatic and Fsiery Sciences, UW, Box 355020, Seattle, WA","active":true,"usgs":false}],"preferred":false,"id":783314,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bhuthimethee, Mary","contributorId":222836,"corporation":false,"usgs":false,"family":"Bhuthimethee","given":"Mary","email":"","affiliations":[{"id":40609,"text":"Seattle Public Utilities, Seattle, WA","active":true,"usgs":false}],"preferred":false,"id":783315,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Winton, James 0000-0002-3505-5509 jwinton@usgs.gov","orcid":"https://orcid.org/0000-0002-3505-5509","contributorId":179330,"corporation":false,"usgs":true,"family":"Winton","given":"James","email":"jwinton@usgs.gov","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":783316,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70209424,"text":"70209424 - 2020 - Geology of the Trout Rock caves (Hamilton Cave, Trout Cave, New Trout Cave) in Pendleton County, West Virginia (USA), and implications regarding the origin of maze caves","interactions":[],"lastModifiedDate":"2020-04-09T17:51:25.200543","indexId":"70209424","displayToPublicDate":"2020-02-26T12:26:03","publicationYear":"2020","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Geology of the Trout Rock caves (Hamilton Cave, Trout Cave, New Trout Cave) in Pendleton County, West Virginia (USA), and implications regarding the origin of maze caves","docAbstract":"<p>The Trout Rock caves (Hamilton Cave, Trout Cave, New Trout Cave) are located in a hill named Cave Knob that overlooks the South Branch of the Potomac River in Pendleton County, West Virginia (U.S.A). The geologic structure of this hill is a northeasttrending anticline, and the caves are located at different elevations primarily along the contact between the Devonian New Creek Limestone (Helderberg Group) and the overlying Devonian Corriganville Limestone (Helderberg Group). The entrance to New Trout Cave (Stop 1) is located on the east flank of Cave Knob anticline at an elevation of 585 m (1,920 ft) relative to sea level, or 39 m (128 ft) above the modern river. Much of the cave consists of passages that extend to the northeast along strike, and many of these passages have developed along primary joints that trend N40E or secondary joints that trend N40W. Sediments in New Trout Cave include mud and sand (some of which was mined for nitrate during the American Civil War), as well as large boulders in the front part of the cave. Gypsum crusts are present in a maze section of the cave ~213 to 305 m (700 to 1,000 ft) from the cave entrance. Excavations in New Trout Cave have produced vertebrate fossils of Rancholabrean age, ~300,000 to 10,000 years Before Present (BP). The entrance to Trout Cave (Stop 2) is located on the east flank of Cave Knob anticline ~100 m (328 ft) northwest of the New Trout Cave entrance at an elevation of 622 m (2,040 ft) relative to sea level, or 76 m (249 ft) above the modern river. Much of the cave consists of passages that extend to the northeast along strike, although a small area of network maze passages is present in the western portion of Trout Cave that is closest to Hamilton Cave. Many of the passages of Trout Cave have developed along primary joints that trend N40E or secondary joints that trend N40W. Sediments in Trout Cave include mud (also mined for nitrate during the American Civil War), as well as large boulders in the front part of the cave. Excavations in the upper levels of Trout Cave have produced vertebrate fossils of Rancholabrean age (~300,000 to 10,000 years BP), whereas excavations in the lower levels of the cave have produced vertebrate fossils of Irvingtonian age (~1,810,000 to 300,000 years BP). The entrance to Hamilton Cave (Stop 3) is located along the axis of Cave Knob anticline ~165 m (540 ft) northwest of the Trout Cave entrance at an elevation of 640 m (2,100 ft) relative to sea level, or 94 m (308 ft) above the modern river. The front (upper) part of Hamilton Cave has a classic network maze pattern that is an angular grid of relatively horizontal passages, most of which follow vertical or near-vertical primary joints that trend N40W and N50W and secondary joints that trend N60W and N80E. This part of the cave lies along the axis of Cave Knob anticline. In contrast, the passages in the back (lower) part of Hamilton Cave lie along the west flank of Cave Knob anticline at ~58 to 85 m (190 to 279 ft) above the modern river. These passages do not display a classic maze pattern, and instead they may be divided into the following two categories: (1) longer northeast-trending passages that are relatively horizontal and follow the strike of the beds; and (2) shorter northwest-trending passages that descend steeply to the west and follow the dip of the beds. Sediments in Hamilton Cave include mud (which was apparently not mined for nitrate during the American Civil War), as well as large boulders in the front part of the cave. Gypsum crusts are present along passage walls of the New Creek Limestone from the Slab Room to the Airblower. Excavations in the front part of Hamilton Cave (maze section) have produced vertebrate fossils of Irvingtonian age (~1,810,000 to 300,000 years BP). The network maze portions of Hamilton Cave are interpreted as having developed at or near the water table where water did not have a free surface in contact with air and where the following conditions were present: (1) Location on or near the axis of an anticline (the location of the greatest amount of flexure); (2) Abundant vertical or near vertical joints, which are favored by location in the area of greatest flexure and by a lithologic unit (chert-rich limestone) that is more likely to experience brittle rather than ductile deformation; (3) Widening of joints to enhance ease of water infiltration, favored by location in area of greatest amount of flexure; and (4) Dissolution along nearly all major joints to produce cave passages of approximately the same size (which would most likely occur via water without a free surface in contact with air). The cave passages that are located along anticline axes and along strike at the New Creek-Corriganville contact are interpreted as having formed initially during times of base level stillstand at or near the water table where water did not have a free surface in contact with air and where the water flowed along the hydraulic gradient at gentle slopes. Under such conditions, dissolution occurred in all directions to produce cave passages with relatively linear wall morphologies. In the lower portions of some of the along-strike passages, the cave walls have a more sinuous (meandering) morphology, which is interpreted as having formed during subsequent initial base level fall as cave development continued under vadose conditions where the water had a free surface in contact with air, and where water flow was governed primarily by gravitational processes. Steeply inclined cave passages that are located along dip at the New Creek-Corriganville contact are interpreted as having formed during subsequent true vadose conditions (after base level fall). This chronology of base level stasis (with cave development in the phreatic zone a short distance below top of water table) followed by base level fall (with cave development in the vadose or epiphreatic zone) has repeated multiple times at Cave Knob during the past ~4 to 3 million years, resulting in multiple cave passages at different elevations, with different passage morphologies, and at different passage locations with respect to strike and dip.</p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Geological Society of America Field Guide","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Geological Society of America","doi":"10.1130/2020.0057(03)","collaboration":"","usgsCitation":"Swezey, C.S., and Brent, E.L., 2020, Geology of the Trout Rock caves (Hamilton Cave, Trout Cave, New Trout Cave) in Pendleton County, West Virginia (USA), and implications regarding the origin of maze caves, chap. <i>of</i> Geological Society of America Field Guide, v. 57, p. 43-77, https://doi.org/10.1130/2020.0057(03).","productDescription":"35 p.","startPage":"43","endPage":"77","ipdsId":"IP-113405","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":457583,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/2020.0057(03)","text":"Publisher Index Page"},{"id":373863,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"West Virginia","county":"Pendleton County","otherGeospatial":"Trout Rock Caves","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -79.06036376953125,\n              38.768004230175954\n            ],\n            [\n              -79.37759399414062,\n              38.975424875431436\n            ],\n            [\n              -79.4586181640625,\n              38.932707274379595\n            ],\n            [\n              -79.53826904296875,\n              38.839707613545144\n            ],\n            [\n              -79.66323852539062,\n              38.59970036588819\n            ],\n            [\n              -79.53414916992186,\n              38.543869175876154\n            ],\n            [\n              -79.47509765625,\n              38.460041065720446\n            ],\n            [\n              -79.33364868164062,\n              38.415938460513274\n            ],\n            [\n              -79.27322387695312,\n              38.41486245064945\n            ],\n            [\n              -79.20867919921875,\n              38.50304202775689\n            ],\n            [\n              -79.21005249023438,\n              38.515937313413474\n            ],\n            [\n              -79.12216186523438,\n              38.66299474019031\n            ],\n            [\n              -79.1015625,\n              38.659777730712534\n            ],\n            [\n              -79.08233642578124,\n              38.6897975322717\n            ],\n            [\n              -79.06036376953125,\n              38.768004230175954\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"57","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Swezey, Christopher S. 0000-0003-4019-9264 cswezey@usgs.gov","orcid":"https://orcid.org/0000-0003-4019-9264","contributorId":173033,"corporation":false,"usgs":true,"family":"Swezey","given":"Christopher","email":"cswezey@usgs.gov","middleInitial":"S.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":786454,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brent, Emily L","contributorId":223860,"corporation":false,"usgs":false,"family":"Brent","given":"Emily","email":"","middleInitial":"L","affiliations":[],"preferred":false,"id":786455,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70211287,"text":"70211287 - 2020 - The role of Northeast Pacific meltwater events in deglacial climate change","interactions":[],"lastModifiedDate":"2020-07-22T15:13:57.928397","indexId":"70211287","displayToPublicDate":"2020-02-26T10:11:20","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5010,"text":"Science Advances","active":true,"publicationSubtype":{"id":10}},"title":"The role of Northeast Pacific meltwater events in deglacial climate change","docAbstract":"Columbia River megafloods occurred repeatedly during the last deglaciation, but the impacts of this fresh water on Pacific hydrography are largely unknown. To reconstruct changes in ocean circulation during this period, we used a numerical model to simulate the flow trajectory of Columbia River megafloods and compiled records of sea surface temperature, paleo-salinity, and deep-water radiocarbon from marine sediment cores in the Northeast Pacific. The North Pacific sea surface cooled and freshened during the early deglacial (19.0-16.5 ka) and Younger Dryas (12.9-11.7 ka) intervals, coincident with the appearance of subsurface water masses depleted in radiocarbon relative to the sea surface. We infer that Pacific meltwater fluxes contributed to net Northern Hemisphere cooling prior to North Atlantic Heinrich Events, and again during the Younger Dryas stadial. Abrupt warming in the Northeast Pacific similarly contributed to hemispheric warming during the Bølling and Holocene transitions. These findings underscore the importance of changes in North Pacific freshwater fluxes and circulation in deglacial climate events.","language":"English","publisher":"AAAS","doi":"10.1126/sciadv.aay2915","usgsCitation":"Praetorius, S.K., Condron, A., Mix, A., Walczak, M., McKay, J., and Du, J., 2020, The role of Northeast Pacific meltwater events in deglacial climate change: Science Advances, v. 6, no. 9, eaay2915, 18 p., https://doi.org/10.1126/sciadv.aay2915.","productDescription":"eaay2915, 18 p.","ipdsId":"IP-093675","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":457590,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1126/sciadv.aay2915","text":"Publisher Index Page"},{"id":376636,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"6","issue":"9","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Praetorius, Summer K. 0000-0003-2683-3652","orcid":"https://orcid.org/0000-0003-2683-3652","contributorId":206966,"corporation":false,"usgs":true,"family":"Praetorius","given":"Summer","email":"","middleInitial":"K.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":793519,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Condron, Alan 0000-0002-7337-1713","orcid":"https://orcid.org/0000-0002-7337-1713","contributorId":229547,"corporation":false,"usgs":false,"family":"Condron","given":"Alan","email":"","affiliations":[{"id":36711,"text":"Woods Hole Oceanographic Institution","active":true,"usgs":false}],"preferred":false,"id":793520,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mix, Alan","contributorId":184163,"corporation":false,"usgs":false,"family":"Mix","given":"Alan","affiliations":[],"preferred":false,"id":793521,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Walczak, Maureen 0000-0002-4123-6998","orcid":"https://orcid.org/0000-0002-4123-6998","contributorId":206972,"corporation":false,"usgs":false,"family":"Walczak","given":"Maureen","email":"","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":793522,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McKay, Jennifer","contributorId":229548,"corporation":false,"usgs":false,"family":"McKay","given":"Jennifer","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":793523,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Du, Jianghui 0000-0002-3386-9314","orcid":"https://orcid.org/0000-0002-3386-9314","contributorId":206970,"corporation":false,"usgs":false,"family":"Du","given":"Jianghui","email":"","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":793524,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70223337,"text":"70223337 - 2020 - Trends in cheetah Acinonyx jubatus density in north-central Namibia","interactions":[],"lastModifiedDate":"2021-08-24T13:13:40.57478","indexId":"70223337","displayToPublicDate":"2020-02-26T08:09:04","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3103,"text":"Population Ecology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Trends in cheetah <i>Acinonyx jubatus</i> density in north-central Namibia","title":"Trends in cheetah Acinonyx jubatus density in north-central Namibia","docAbstract":"<div class=\"abstract-group\"><div class=\"article-section__content en main\"><p>Assessing trends in abundance and density of species of conservation concern is vital to inform conservation and management strategies. The remaining population of the cheetah (<i>Acinonyx jubatus</i>) largely exists outside of protected areas, where they are often in conflict with humans. Despite this, the population status and dynamics of cheetah outside of protected areas have received relatively limited attention across its range. We analyzed remote camera trapping data of nine surveys conducted from 2005 to 2014 in the Waterberg Conservancy, north-central Namibia, which included detections of 74 individuals (52 adult males, 7 adult females and 15 dependents). Using spatial capture–recapture methods, we assessed annual and seasonal trends in cheetah density. We found evidence of a stable trend in cheetah density over the study period, with an average density of 1.94/100 km<sup>2</sup><span>&nbsp;</span>(95% confidence interval 1.33–2.84). This apparent stability of cheetah density is likely the result of stable and abundant prey availability, a high tolerance to carnivores by farmers and low turnover rates in home range tenure. This study highlights the importance of promoting long-term surveys that capture a broad range of environmental variation that may influence species density and the importance of nonprotected areas for cheetah conservation.</p></div></div>","language":"English","publisher":"Wiley","doi":"10.1002/1438-390X.12045","usgsCitation":"Fabiano, E.C., Sutherland, C., Fuller, A.K., Nghikembua, M., Eizirik, E., and Marker, L., 2020, Trends in cheetah Acinonyx jubatus density in north-central Namibia: Population Ecology, v. 62, no. 2, p. 233-243, https://doi.org/10.1002/1438-390X.12045.","productDescription":"11 p.","startPage":"233","endPage":"243","ipdsId":"IP-102240","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":388416,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Namibia","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[16.34498,-28.57671],[15.60182,-27.82125],[15.21047,-27.09096],[14.98971,-26.11737],[14.74321,-25.39292],[14.40814,-23.85301],[14.38572,-22.65665],[14.25771,-22.11121],[13.86864,-21.69904],[13.3525,-20.87283],[12.82685,-19.67317],[12.60856,-19.04535],[11.79492,-18.06913],[11.7342,-17.30189],[12.21546,-17.11167],[12.81408,-16.94134],[13.46236,-16.97121],[14.0585,-17.42338],[14.20971,-17.3531],[18.26331,-17.30995],[18.95619,-17.78909],[21.37718,-17.93064],[23.21505,-17.52312],[24.03386,-17.29584],[24.68235,-17.35341],[25.07695,-17.57882],[25.08444,-17.66182],[24.52071,-17.88712],[24.21736,-17.88935],[23.57901,-18.28126],[23.19686,-17.86904],[21.65504,-18.21915],[20.91064,-18.25222],[20.88113,-21.81433],[19.89546,-21.84916],[19.89577,-24.76779],[19.89473,-28.4611],[19.00213,-28.97244],[18.4649,-29.04546],[17.83615,-28.85638],[17.3875,-28.78351],[17.21893,-28.35594],[16.82402,-28.08216],[16.34498,-28.57671]]]},\"properties\":{\"name\":\"Namibia\"}}]}","volume":"62","issue":"2","noUsgsAuthors":false,"publicationDate":"2020-02-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Fabiano, Ezequiel Chimbioputo","contributorId":264636,"corporation":false,"usgs":false,"family":"Fabiano","given":"Ezequiel","email":"","middleInitial":"Chimbioputo","affiliations":[{"id":54520,"text":"University of Nambia","active":true,"usgs":false}],"preferred":false,"id":821801,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sutherland, Chris","contributorId":264637,"corporation":false,"usgs":false,"family":"Sutherland","given":"Chris","affiliations":[{"id":36396,"text":"University of Massachusetts","active":true,"usgs":false}],"preferred":false,"id":821802,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fuller, Angela K. 0000-0002-9247-7468 afuller@usgs.gov","orcid":"https://orcid.org/0000-0002-9247-7468","contributorId":3984,"corporation":false,"usgs":true,"family":"Fuller","given":"Angela","email":"afuller@usgs.gov","middleInitial":"K.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":821800,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nghikembua, Matti","contributorId":264638,"corporation":false,"usgs":false,"family":"Nghikembua","given":"Matti","email":"","affiliations":[{"id":54521,"text":"Cheetah Conservation Fund","active":true,"usgs":false}],"preferred":false,"id":821803,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Eizirik, Eduardo","contributorId":264639,"corporation":false,"usgs":false,"family":"Eizirik","given":"Eduardo","affiliations":[{"id":54522,"text":"Pontifícia UniversidadeCatólicadoRio Grandedo Sul","active":true,"usgs":false}],"preferred":false,"id":821804,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Marker, Laurie","contributorId":264640,"corporation":false,"usgs":false,"family":"Marker","given":"Laurie","email":"","affiliations":[{"id":54521,"text":"Cheetah Conservation Fund","active":true,"usgs":false}],"preferred":false,"id":821805,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70207592,"text":"sir20195147 - 2020 - Water withdrawals, uses, and trends in Florida, 2015","interactions":[],"lastModifiedDate":"2022-04-25T20:27:23.096539","indexId":"sir20195147","displayToPublicDate":"2020-02-26T07:43:08","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2019-5147","displayTitle":"Water Withdrawals, Uses, and Trends in Florida, 2015","title":"Water withdrawals, uses, and trends in Florida, 2015","docAbstract":"<p>In 2015, the total amount of water withdrawn in Florida was estimated to be 15,319 million gallons per day (Mgal/d). Saline water accounted for 9,598 Mgal/d (63 percent) and freshwater accounted for 5,721 Mgal/d (37 percent) of the total. Groundwater accounted for 3,604 Mgal/d (63 percent) of freshwater withdrawals and surface water accounted for the remaining 2,117 Mgal/d (37 percent). Surface-water sources accounted for 9,401 Mgal/d (98 percent) of the saline-water withdrawals, and groundwater sources accounted for the remaining 198 Mgal/d (2 percent). The majority of groundwater withdrawals (almost 62 percent) in 2015 were from the Floridan aquifer system, which is used throughout most of the State while the majority of fresh surface-water withdrawals (52 percent) occurred in the Southern Florida Subregion, a hydrologic unit that includes Lake Okeechobee and canals in the Everglades Agricultural Area. Groundwater provided drinking water (public supplied and self-supplied) for 18.324 million people (92 percent of Florida’s population), and fresh surface water provided drinking water for 1.491 million people (8 percent).</p><p>Overall, public supply accounted for 39 percent of the total freshwater withdrawals (ground and surface) and 53 percent of groundwater withdrawals, followed by agricultural self-supplied uses, which accounted for 37 percent of the total freshwater withdrawals and 28 percent of groundwater withdrawals. Other self-supplied groundwater withdrawals include commercial-industrial-mining self-supplied (8 percent), recreational-landscape irrigation and domestic self-supplied (5 percent each), and power generation (less than 1 percent). Agricultural self-supplied withdrawals accounted for 51 percent of fresh surface-water withdrawals, followed by power generation (19 percent), public supply (15 percent), recreational-landscape irrigation (10 percent), and commercial-industrial-mining self-supplied (5 percent).</p><p>In 1975, agricultural water withdrawals accounted for 43 percent of the total freshwater withdrawals, followed by power generation (24 percent) and public supply (17 percent). By 2000, agricultural withdrawals increased to 48 percent of the total freshwater withdrawals, followed by public supply (30 percent). For 2015, agricultural self-supplied decreased to 37 percent of total freshwater withdrawals, and was surpassed by public supply at 39 percent. Over the 40-year period between 1975 and 2015, increases in freshwater withdrawals caused by large gains in population and the expansion of irrigated acreage were offset by decreases in water used for power generation and commercial-industrial-mining withdrawals. Since 2000, however, irrigated acreage has decreased statewide because of crop disease, storm damage, and urbanization. This decline, coupled with large gains in water conservation measures in the farming industry, has led to agricultural withdrawals in Florida being less than public-supply withdrawals for the first time since water-use data were first reported in 1965.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195147","collaboration":"Prepared in cooperation with the Florida Department of Agricultural and Consumer Services","usgsCitation":"Marella, R.L., 2020, Water withdrawals, uses, and trends in Florida, 2015: U.S. Geological Survey Scientific Investigations Report 2019–5147, 52 p., https://doi.org/10.3133/sir20195147.","productDescription":"Report: vii, 52 p.; Data Release","numberOfPages":"64","onlineOnly":"Y","ipdsId":"IP-093230","costCenters":[{"id":27821,"text":"Caribbean-Florida Water Science 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 \"}}]}","contact":"<p>Director, <a data-mce-href=\"https://www2.usgs.gov/water/caribbeanflorida/index.html\" href=\"https://www2.usgs.gov/water/caribbeanflorida/index.html\">Caribbean-Florida Water Science Center</a> <br>U.S. Geological Survey <br>4446 Pet Lane, Suite 108 <br>Lutz, FL 33559</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Water Withdrawals and Use</li><li>Water Withdrawal and Use Trends for Florida, 1950–2010</li><li>Summary</li><li>References Cited</li><li>Glossary</li></ul>","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"publishedDate":"2020-02-26","noUsgsAuthors":false,"publicationDate":"2020-02-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Marella, Richard L. 0000-0003-4861-9841","orcid":"https://orcid.org/0000-0003-4861-9841","contributorId":221550,"corporation":false,"usgs":true,"family":"Marella","given":"Richard","email":"","middleInitial":"L.","affiliations":[{"id":5051,"text":"FLWSC-Orlando","active":true,"usgs":true}],"preferred":true,"id":778628,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70209900,"text":"70209900 - 2020 - How repeatable is CTmax within individual brook trout over short- and long-time intervals?","interactions":[],"lastModifiedDate":"2020-05-06T12:16:07.524556","indexId":"70209900","displayToPublicDate":"2020-02-26T07:14:53","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2476,"text":"Journal of Thermal Biology","active":true,"publicationSubtype":{"id":10}},"title":"How repeatable is CTmax within individual brook trout over short- and long-time intervals?","docAbstract":"As stream temperatures increase due to factors such as heated runoff from impervious surfaces, deforestation, and climate change, fish species adapted to cold water streams are forced to move to more suitable habitat, acclimate or adapt to increased thermal regimes, or die. To estimate the potential for adaptation, a (within individual) repeatable metric of thermal tolerance is imperative. Critical thermal maximum (CTmax) is a dynamic test that is widely used to measure thermal tolerance across many taxa and has been used in fishes for decades, but its repeatability in most species is unknown.   CTmax tests increase water temperature steadily over time until loss of equilibrium (LOE) is achieved. To determine if CTmax is a consistent metric within individual fish, we measured CTmax on the same lab-held individually-marked adult brook trout Salvelinus fontinalis at three different times (August & September 2016, September 2017). We found that CTmax is a repeatable trait (Repeatability ± S.E.: 0.48 ± 0.14).   CTmax of individuals males was consistent over time, but the CTmax of females increased slightly over time. This result indicates that CTmax is a robust, repeatable estimate of thermal tolerance in a cold-water adapted fish.","language":"English","publisher":"Elsevier","doi":"10.1016/j.jtherbio.2020.102559","collaboration":"","usgsCitation":"O’Donnell, M.J., Regish, A.M., McCormick, S.D., and Letcher, B., 2020, How repeatable is CTmax within individual brook trout over short- and long-time intervals?: Journal of Thermal Biology, v. 89, 102559, 6p., https://doi.org/10.1016/j.jtherbio.2020.102559.","productDescription":"102559, 6p.","ipdsId":"IP-108628","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":457596,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jtherbio.2020.102559","text":"Publisher Index Page"},{"id":374484,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"89","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"O’Donnell, Matthew J. 0000-0002-9089-2377 modonnell@usgs.gov","orcid":"https://orcid.org/0000-0002-9089-2377","contributorId":2003,"corporation":false,"usgs":true,"family":"O’Donnell","given":"Matthew","email":"modonnell@usgs.gov","middleInitial":"J.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":false,"id":788548,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Regish, Amy M. 0000-0003-4747-4265 aregish@usgs.gov","orcid":"https://orcid.org/0000-0003-4747-4265","contributorId":5415,"corporation":false,"usgs":true,"family":"Regish","given":"Amy","email":"aregish@usgs.gov","middleInitial":"M.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":788549,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McCormick, Stephen D. 0000-0003-0621-6200 smccormick@usgs.gov","orcid":"https://orcid.org/0000-0003-0621-6200","contributorId":139214,"corporation":false,"usgs":true,"family":"McCormick","given":"Stephen","email":"smccormick@usgs.gov","middleInitial":"D.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":788550,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Letcher, Benjamin H. 0000-0003-0191-5678 bletcher@usgs.gov","orcid":"https://orcid.org/0000-0003-0191-5678","contributorId":167313,"corporation":false,"usgs":true,"family":"Letcher","given":"Benjamin H.","email":"bletcher@usgs.gov","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":false,"id":788551,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70208399,"text":"fs20203009 - 2020 - Water-quality comparison of the Gulf Coast aquifer system and Carrizo-Wilcox aquifer in Texas from National Water-Quality Assessment Project Principal Aquifer Surveys, 2013 and 2015","interactions":[],"lastModifiedDate":"2022-04-20T18:25:46.361216","indexId":"fs20203009","displayToPublicDate":"2020-02-25T15:26:57","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2020-3009","displayTitle":"Water-Quality Comparison of the Gulf Coast Aquifer System and Carrizo-Wilcox Aquifer in Texas From National Water-Quality Assessment Project Principal Aquifer Surveys, 2013 and 2015","title":"Water-quality comparison of the Gulf Coast aquifer system and Carrizo-Wilcox aquifer in Texas from National Water-Quality Assessment Project Principal Aquifer Surveys, 2013 and 2015","docAbstract":"<p>The U.S. Geological Survey’s National Water-Quality Assessment (NAWQA) Project assessed the quality of groundwater in aquifers that are important sources of drinking water in the United States. One major aquifer in Texas that was assessed by NAWQA in 2013 is the coastal lowlands aquifer system, which is often referred to in Texas as the “Gulf Coast aquifer system.” The coastal lowlands aquifer system supplies water for millions of people; self-supplied (private) well withdrawals in 2005 from this aquifer system were the sixth largest among all major aquifer systems in the Nation. A major aquifer in Texas that was assessed by NAWQA in 2015 is the Texas coastal uplands aquifer system; the Carrizo-Wilcox aquifer is one of several aquifers that compose this aquifer system in Texas. The rocks composing the Texas coastal uplands aquifer system extend east from Texas as part of the Mississippi embayment aquifer system and underlie areas of several States. The Texas coastal uplands aquifer system and Mississippi embayment aquifer system are often collectively referred to as the “Mississippi embayment-Texas coastal uplands aquifer system.” Self-supplied withdrawals from the Mississippi embayment-Texas coastal uplands aquifer system in 2005 were the eighth largest among all major aquifer systems in the Nation. The coastal lowlands aquifer system and Mississippi embayment-Texas coastal uplands aquifer system were assessed as part of the NAWQA Principal Aquifer Surveys (PAS), which were designed to evaluate constituent concentrations in water samples obtained from domestic and public-supply wells prior to any treatment. PAS assessments like these allow for the comparison of water-quality concentrations in untreated groundwater using preestablished benchmarks for the protection of human health and for aesthetic qualities such as taste, color, and odor. The use of preestablished benchmarks can provide a basis for comparison of groundwater quality among principal aquifers.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20203009","collaboration":"U.S. Geological Survey National Water-Quality Assessment","usgsCitation":"Ging, P.B., 2020, Water-quality comparison of the Gulf Coast aquifer system and Carrizo-Wilcox aquifer in Texas from National Water-Quality Assessment Project Principal Aquifer Surveys, 2013 and 2015: U.S. Geological Survey Fact Sheet 2020–3009, 4 p., https://doi.org/10.3133/fs20203009.","productDescription":"4 p.","numberOfPages":"4","onlineOnly":"N","ipdsId":"IP-111986","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":399199,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109727.htm"},{"id":372560,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2020/3009/fs20203009.pdf","text":"Report","size":"1.01 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 20220–3009"},{"id":372559,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2020/3009/coverthb.jpg"}],"country":"United States","state":"Texas","otherGeospatial":"Gulf Coast aquifer system, Carrizo-Wilcox aquifer","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -100.5,\n              25.8378\n            ],\n            [\n              -93.5069,\n              25.8378\n            ],\n            [\n              -93.5069,\n              33.5433\n            ],\n            [\n              -100.5,\n              33.5433\n            ],\n            [\n              -100.5,\n              25.8378\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p>Director, <a data-mce-href=\"https://www.usgs.gov/centers/tx-water\" href=\"https://www.usgs.gov/centers/tx-water\">Oklahoma-Texas Water Science Center</a><br>U.S. Geological Survey<br>1505 Ferguson Lane <br>Austin, TX 78754–4501 </p>","tableOfContents":"<ul><li>Overview of Water-Quality Sampling and Benchmarks for Evaluating Groundwater Quality</li><li>Water-Quality Results for the Gulf Coast Aquifer System and Carrizo-Wilcox Aquifer</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"publishedDate":"2020-02-25","noUsgsAuthors":false,"publicationDate":"2020-02-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Ging, Patricia B. 0000-0001-5491-8448","orcid":"https://orcid.org/0000-0001-5491-8448","contributorId":222263,"corporation":false,"usgs":true,"family":"Ging","given":"Patricia","email":"","middleInitial":"B.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":781732,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70221837,"text":"70221837 - 2020 - Machine learning identifies a strong association between warming and reduced primary productivity in an oligotrophic ocean gyre","interactions":[],"lastModifiedDate":"2021-07-09T19:30:10.52931","indexId":"70221837","displayToPublicDate":"2020-02-25T14:24:57","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":"Machine learning identifies a strong association between warming and reduced primary productivity in an oligotrophic ocean gyre","docAbstract":"<p><span>Phytoplankton play key roles in the oceans by regulating global biogeochemical cycles and production in marine food webs. Global warming is thought to affect phytoplankton production both directly, by impacting their photosynthetic metabolism, and indirectly by modifying the physical environment in which they grow. In this respect, the Bermuda Atlantic Time-series Study (BATS) in the Sargasso Sea (North Atlantic gyre) provides a unique opportunity to explore effects of warming on phytoplankton production across the vast oligotrophic ocean regions because it is one of the few multidecadal records of measured net primary productivity (NPP). We analysed the time series of phytoplankton primary productivity at BATS site using machine learning techniques (ML) to show that increased water temperature over a 27-year period (1990–2016), and the consequent weakening of vertical mixing in the upper ocean, induced a negative feedback on phytoplankton productivity by reducing the availability of essential resources, nitrogen and light. The unbalanced availability of these resources with warming, coupled with ecological changes at the community level, is expected to intensify the oligotrophic state of open-ocean regions that are far from land-based nutrient sources.</span></p>","language":"English","publisher":"Nature Publications","doi":"10.1038/s41598-020-59989-y","usgsCitation":"D’Alelio, D., Rampone, S., Cusano, L.M., Morfino, V., Russo, L., Sanseverino, N., Cloern, J.E., and Lomas, M.W., 2020, Machine learning identifies a strong association between warming and reduced primary productivity in an oligotrophic ocean gyre: Scientific Reports, v. 10, 3287, 12 p., https://doi.org/10.1038/s41598-020-59989-y.","productDescription":"3287, 12 p.","ipdsId":"IP-111898","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":457603,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-020-59989-y","text":"Publisher Index Page"},{"id":387061,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"North Atlantic Gyre","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -64.3359375,\n              23.885837699862005\n            ],\n            [\n              -38.84765625,\n              28.613459424004414\n            ],\n            [\n              -19.51171875,\n              34.016241889667015\n            ],\n            [\n              -17.75390625,\n              41.11246878918088\n            ],\n            [\n              -26.3671875,\n              47.754097979680026\n            ],\n            [\n              -41.66015625,\n              46.6795944656402\n            ],\n            [\n              -61.17187499999999,\n              39.639537564366684\n            ],\n            [\n              -69.78515625,\n              35.31736632923788\n            ],\n            [\n              -76.9921875,\n              31.203404950917395\n            ],\n            [\n              -75.41015624999999,\n              26.902476886279832\n            ],\n            [\n              -71.54296874999999,\n              23.563987128451217\n            ],\n            [\n              -64.3359375,\n              23.885837699862005\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"10","noUsgsAuthors":false,"publicationDate":"2020-02-25","publicationStatus":"PW","contributors":{"authors":[{"text":"D’Alelio, Domenico","contributorId":260813,"corporation":false,"usgs":false,"family":"D’Alelio","given":"Domenico","email":"","affiliations":[{"id":27945,"text":"Stazione Zoologica Anton Dohrn","active":true,"usgs":false}],"preferred":false,"id":818883,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rampone, Salvatore","contributorId":260814,"corporation":false,"usgs":false,"family":"Rampone","given":"Salvatore","email":"","affiliations":[{"id":52676,"text":"Università degli Studi del Sannio","active":true,"usgs":false}],"preferred":false,"id":818884,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cusano, Luigi Maria","contributorId":260815,"corporation":false,"usgs":false,"family":"Cusano","given":"Luigi","email":"","middleInitial":"Maria","affiliations":[{"id":52676,"text":"Università degli Studi del Sannio","active":true,"usgs":false}],"preferred":false,"id":818885,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Morfino, Valerio","contributorId":260816,"corporation":false,"usgs":false,"family":"Morfino","given":"Valerio","email":"","affiliations":[{"id":52676,"text":"Università degli Studi del Sannio","active":true,"usgs":false}],"preferred":false,"id":818886,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Russo, Luca","contributorId":260817,"corporation":false,"usgs":false,"family":"Russo","given":"Luca","email":"","affiliations":[{"id":27945,"text":"Stazione Zoologica Anton Dohrn","active":true,"usgs":false}],"preferred":false,"id":818887,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sanseverino, Nadia","contributorId":260818,"corporation":false,"usgs":false,"family":"Sanseverino","given":"Nadia","email":"","affiliations":[{"id":52676,"text":"Università degli Studi del Sannio","active":true,"usgs":false}],"preferred":false,"id":818888,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Cloern, James E. 0000-0002-5880-6862 jecloern@usgs.gov","orcid":"https://orcid.org/0000-0002-5880-6862","contributorId":1488,"corporation":false,"usgs":true,"family":"Cloern","given":"James","email":"jecloern@usgs.gov","middleInitial":"E.","affiliations":[{"id":438,"text":"National Research Program - 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,{"id":70209079,"text":"70209079 - 2020 - Prioritizing water security in the management of vector borne diseases: Lessons from Oaxaca, Mexico","interactions":[],"lastModifiedDate":"2020-03-16T06:18:12","indexId":"70209079","displayToPublicDate":"2020-02-25T14:22:00","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5050,"text":"Geohealth News","active":true,"publicationSubtype":{"id":10}},"title":"Prioritizing water security in the management of vector borne diseases: Lessons from Oaxaca, Mexico","docAbstract":"Changes in human water use, along with temperature and rainfall patterns, are facilitating habitat spread and distribution of Aedes aegypti and Aedes albopictus mosquitoes, the primary vectors for the transmission of Dengue, Chikungunya, and Zika viruses in the Americas. Artificial containers and wetspots provide major sources of mosquito larval habitat in residential areas. Mosquito abatement and control strategies remain the most effective public health interventions for minimizing the impact of these vector borne diseases. Understanding how water insecurity is conducive to the establishment and elimination of endemic mosquito populations, particularly in arid or semi-arid regions, is a vital component in shaping these intervention strategies.","language":"English","publisher":"AGU","doi":"10.1029/2019gh000201","usgsCitation":"Akanda, A.S., Johnson, K.D., Ginsberg, H., and Couret, J., 2020, Prioritizing water security in the management of vector borne diseases: Lessons from Oaxaca, Mexico: Geohealth News, v. 4, no. 3, e2019GH000201, 5 p., https://doi.org/10.1029/2019gh000201.","productDescription":"e2019GH000201, 5 p.","ipdsId":"IP-112940","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":457606,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2019gh000201","text":"Publisher Index Page"},{"id":373277,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Mexico","city":"Oaxaca","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -97.18505859374999,\n              16.74142754700361\n            ],\n            [\n              -95.877685546875,\n              16.74142754700361\n            ],\n            [\n              -95.877685546875,\n              17.403062993328923\n            ],\n            [\n              -97.18505859374999,\n              17.403062993328923\n            ],\n            [\n              -97.18505859374999,\n              16.74142754700361\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"4","issue":"3","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2020-03-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Akanda, Ali S","contributorId":223365,"corporation":false,"usgs":false,"family":"Akanda","given":"Ali","email":"","middleInitial":"S","affiliations":[{"id":6922,"text":"University of Rhode Island","active":true,"usgs":false}],"preferred":false,"id":784850,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, Kristine D.","contributorId":168716,"corporation":false,"usgs":false,"family":"Johnson","given":"Kristine","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":784851,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ginsberg, Howard S. 0000-0002-4933-2466 hginsberg@usgs.gov","orcid":"https://orcid.org/0000-0002-4933-2466","contributorId":147665,"corporation":false,"usgs":true,"family":"Ginsberg","given":"Howard S.","email":"hginsberg@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":784849,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Couret, Janelle","contributorId":194159,"corporation":false,"usgs":false,"family":"Couret","given":"Janelle","affiliations":[],"preferred":false,"id":784852,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70218295,"text":"70218295 - 2020 - A non-intrusive approach for efficient stochastic emulation and optimization of model-based nitrate-loading management decision support","interactions":[],"lastModifiedDate":"2021-02-23T13:39:06.774641","indexId":"70218295","displayToPublicDate":"2020-02-25T07:36:55","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1551,"text":"Environmental Modelling and Software","active":true,"publicationSubtype":{"id":10}},"title":"A non-intrusive approach for efficient stochastic emulation and optimization of model-based nitrate-loading management decision support","docAbstract":"<div id=\"abstracts\" class=\"Abstracts u-font-serif\"><div id=\"abs0010\" class=\"abstract author\" lang=\"en\"><div id=\"abssec0010\"><p id=\"abspara0010\">Use of physically-motivated numerical models like groundwater flow-and-transport models for probabilistic impact assessments and optimization under uncertainty (OUU) typically incurs such a computational burdensome that these tools cannot be used during decision making. The computational challenges associated with these models can be addressed through emulation. In the land-use/water-quality context, the linear relation between nitrate loading and surface-water/groundwater nitrate concentrations presents an opportunity for employing an efficient model emulator through the application of impulse-response matrices. When paired with first-order second-moment techniques, the emulation strategy gives rise to the “stochastic impulse-response emulator” (SIRE). SIRE is shown to facilitate non-intrusive, near-real time, and risk-based evaluation of nitrate-loading change scenarios, as well as nitrate-loading OUU subject to surface-water/groundwater concentration constraints in high decision variable and parameter dimensions. Two case studies are used to demonstrate SIRE in the nitrate-loading context.</p></div></div></div><ul id=\"issue-navigation\" class=\"issue-navigation u-margin-s-bottom u-bg-grey1\"></ul>","language":"English","publisher":"Elsevier","doi":"10.1016/j.envsoft.2020.104657","usgsCitation":"White, J., Knowling, M., Fienen, M., Feinstein, D.T., McDonald, G.W., and Moore, C.R., 2020, A non-intrusive approach for efficient stochastic emulation and optimization of model-based nitrate-loading management decision support: Environmental Modelling and Software, v. 126, 104657, 11 p., https://doi.org/10.1016/j.envsoft.2020.104657.","productDescription":"104657, 11 p.","ipdsId":"IP-106798","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":383595,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"126","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"White, Jeremy T. 0000-0002-4950-1469","orcid":"https://orcid.org/0000-0002-4950-1469","contributorId":214251,"corporation":false,"usgs":false,"family":"White","given":"Jeremy T.","affiliations":[{"id":36277,"text":"GNS Science","active":true,"usgs":false}],"preferred":false,"id":810890,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Knowling, Matthew 0000-0002-7273-3495","orcid":"https://orcid.org/0000-0002-7273-3495","contributorId":251904,"corporation":false,"usgs":false,"family":"Knowling","given":"Matthew","email":"","affiliations":[{"id":36277,"text":"GNS Science","active":true,"usgs":false}],"preferred":false,"id":810891,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fienen, Michael N. 0000-0002-7756-4651","orcid":"https://orcid.org/0000-0002-7756-4651","contributorId":245632,"corporation":false,"usgs":true,"family":"Fienen","given":"Michael N.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":810892,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Feinstein, Daniel T. 0000-0003-1151-2530 dtfeinst@usgs.gov","orcid":"https://orcid.org/0000-0003-1151-2530","contributorId":1907,"corporation":false,"usgs":true,"family":"Feinstein","given":"Daniel","email":"dtfeinst@usgs.gov","middleInitial":"T.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":810893,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McDonald, Garry W. 0000-0003-3746-4346","orcid":"https://orcid.org/0000-0003-3746-4346","contributorId":251906,"corporation":false,"usgs":false,"family":"McDonald","given":"Garry","email":"","middleInitial":"W.","affiliations":[{"id":50421,"text":"Market Economics","active":true,"usgs":false}],"preferred":false,"id":810894,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Moore, Catherine R.","contributorId":251908,"corporation":false,"usgs":false,"family":"Moore","given":"Catherine","email":"","middleInitial":"R.","affiliations":[{"id":36277,"text":"GNS Science","active":true,"usgs":false}],"preferred":false,"id":810895,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70218283,"text":"70218283 - 2020 - A non-intrusive approach for efficient stochastic emulation and optimization of model-based nitrate-loading management decision support","interactions":[],"lastModifiedDate":"2021-02-24T13:11:27.323218","indexId":"70218283","displayToPublicDate":"2020-02-25T06:51:10","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7599,"text":"Environmental Modeling and Software","active":true,"publicationSubtype":{"id":10}},"title":"A non-intrusive approach for efficient stochastic emulation and optimization of model-based nitrate-loading management decision support","docAbstract":"<p><span>Use of physically-motivated numerical models like groundwater flow-and-transport models for probabilistic impact assessments and optimization under uncertainty (OUU) typically incurs such a computational burdensome that these tools cannot be used during decision making. The computational challenges associated with these models can be addressed through emulation. In the land-use/water-quality context, the linear relation between nitrate loading and surface-water/groundwater nitrate concentrations presents an opportunity for employing an efficient model emulator through the application of impulse-response matrices. When paired with first-order second-moment techniques, the emulation strategy gives rise to the “stochastic impulse-response emulator” (SIRE). SIRE is shown to facilitate non-intrusive, near-real time, and risk-based evaluation of nitrate-loading change scenarios, as well as nitrate-loading OUU subject to surface-water/groundwater concentration constraints in high decision variable and parameter dimensions. Two case studies are used to demonstrate SIRE in the nitrate-loading context.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.envsoft.2020.104657","usgsCitation":"White, J., Knowling, M.J., Fienen, M., Feinstein, D.T., McDonald, G.W., and Catherine R. Moore, 2020, A non-intrusive approach for efficient stochastic emulation and optimization of model-based nitrate-loading management decision support: Environmental Modeling and Software, v. 126, 104657, 11 p., https://doi.org/10.1016/j.envsoft.2020.104657.","productDescription":"104657, 11 p.","ipdsId":"IP-114822","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":383585,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"New Zealand","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              175.31982421875,\n              -37.65120864327175\n            ],\n            [\n              175.70159912109375,\n              -37.65120864327175\n            ],\n            [\n              175.70159912109375,\n              -37.208456662000174\n            ],\n            [\n              175.31982421875,\n              -37.208456662000174\n            ],\n            [\n              175.31982421875,\n              -37.65120864327175\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"126","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"White, Jeremy T. 0000-0002-4950-1469","orcid":"https://orcid.org/0000-0002-4950-1469","contributorId":214251,"corporation":false,"usgs":false,"family":"White","given":"Jeremy T.","affiliations":[{"id":36277,"text":"GNS Science","active":true,"usgs":false}],"preferred":false,"id":810818,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Knowling, Matthew J.","contributorId":251909,"corporation":false,"usgs":false,"family":"Knowling","given":"Matthew","email":"","middleInitial":"J.","affiliations":[{"id":36277,"text":"GNS Science","active":true,"usgs":false}],"preferred":false,"id":810819,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fienen, Michael N. 0000-0002-7756-4651","orcid":"https://orcid.org/0000-0002-7756-4651","contributorId":245632,"corporation":false,"usgs":true,"family":"Fienen","given":"Michael N.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":810820,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Feinstein, Daniel T. 0000-0003-1151-2530 dtfeinst@usgs.gov","orcid":"https://orcid.org/0000-0003-1151-2530","contributorId":1907,"corporation":false,"usgs":true,"family":"Feinstein","given":"Daniel","email":"dtfeinst@usgs.gov","middleInitial":"T.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":810821,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McDonald, Garry W. 0000-0003-3746-4346","orcid":"https://orcid.org/0000-0003-3746-4346","contributorId":251906,"corporation":false,"usgs":false,"family":"McDonald","given":"Garry","email":"","middleInitial":"W.","affiliations":[{"id":50421,"text":"Market Economics","active":true,"usgs":false}],"preferred":false,"id":810822,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Catherine R. 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,{"id":70208691,"text":"70208691 - 2020 - Regional ocean models indicate changing limits to biological invasions in the Bering Sea","interactions":[],"lastModifiedDate":"2020-02-24T19:04:31","indexId":"70208691","displayToPublicDate":"2020-02-24T19:01:23","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1936,"text":"ICES Journal of Marine Science","active":true,"publicationSubtype":{"id":10}},"title":"Regional ocean models indicate changing limits to biological invasions in the Bering Sea","docAbstract":"Minimal vessel traffic and cold water temperatures are believed to limit non-indigenous species (NIS) in high-latitude ecosystems. We evaluated whether suitable conditions exist in the Bering Sea for the introduction, survival, and reproduction of NIS. We compiled temperature and salinity thresholds of known NIS and compared these to ocean conditions projected during two study periods: current (2003-2012) and mid-century (2030-2039). We also explored patterns of vessel traffic and connectivity for U.S. Bering Sea ports. We found the southeastern Bering Sea had suitable conditions for the year-round survival of 80% of NIS assessed (n=42). However, only 52% of NIS had conditions suitable for reproduction or development (n=25). Conditions north of 58° N that include sub-zero winter water temperatures were unsuitable for the survival and reproduction of most NIS. While mid-century models predicted a northward expansion of suitable conditions, conditions for reproduction remained marginal. Within the highly suitable southeastern Bering Sea is the port of Dutch Harbor, which received the most vessel arrivals and ballast water discharge in the U.S. Bering Sea. 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MFEB","active":true,"usgs":true}],"preferred":true,"id":783023,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Watson, Jordan 0000-0002-1686-0377","orcid":"https://orcid.org/0000-0002-1686-0377","contributorId":222313,"corporation":false,"usgs":false,"family":"Watson","given":"Jordan","email":"","affiliations":[{"id":40517,"text":"NOAA Alaska Fisheries Science Center Auke Bay Laboratories","active":true,"usgs":false}],"preferred":false,"id":783026,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Reimer, Jesika","contributorId":222724,"corporation":false,"usgs":false,"family":"Reimer","given":"Jesika","email":"","affiliations":[{"id":40516,"text":"Alaska Center for Conservation Science University of Alaska Anchorage","active":true,"usgs":false}],"preferred":false,"id":783025,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70208409,"text":"sir20205011 - 2020 - Hydrologic and hydraulic analyses of selected streams in Stark County, Ohio","interactions":[],"lastModifiedDate":"2022-04-25T21:37:51.100623","indexId":"sir20205011","displayToPublicDate":"2020-02-24T12:42:30","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2020-5011","displayTitle":"Hydrologic and Hydraulic Analyses of Selected Streams in Stark County, Ohio","title":"Hydrologic and hydraulic analyses of selected streams in Stark County, Ohio","docAbstract":"<p>To update and expand a part of the Federal Emergency Management Agency Flood Insurance Study, the U.S. Geological Survey, the Muskingum Watershed Conservancy District, and the Stark County Commissioners began a cooperative study. The study consisted of hydrologic and hydraulic analyses for selected reaches of 14 streams in Stark County, Ohio: Broad-Monter Creek, Chatham Ditch, East Branch Nimishillen Creek, Fairhope Ditch, Firestone Ditch, Hayden Ditch, Middle Branch Nimishillen Creek, Middle Branch Nimishillen Creek Tributary Number 1, Nimishillen Creek, Reemsnyder Ditch, Sherrick Run, unnamed stream, West Branch Nimishillen Creek, and Zimber Ditch. The study totaled nearly 50 miles of stream reaches.</p><p>Instantaneous peak streamflows for floods with 10-, 4-, 2-, 1-, and 0.2-percent and 1-percent plus annual exceedance probabilities were estimated using historical streamflow data from the streamgages Nimishillen Creek at North Industry, Ohio (U.S. Geological Survey station number 03118500), and Middle Branch Nimishillen Creek at Canton, Ohio (U.S. Geological Survey station number 03118000), regional flood regression equations, and streamflow urbanization techniques.</p><p>The annual exceedance probability streamflows were then used in a Hydrologic Engineering Center-River Analysis System step-backwater model to determine water-surface profiles, flood-inundation boundaries for the 10-, 4-, 2-, 1-, and 0.2-percent and 1-percent plus annual exceedance probability floods, and a regulatory floodway along a selected reach of each stream. Model input included DEM-derived cross sections supplemented with field surveys of open channel cross sections and hydraulic structures, field estimates of roughness values, and annual exceedance probability flood estimates from regional regression equations and historical streamflow data. Flood-inundation boundaries were mapped for the 1- and 0.2-percent annual exceedance probability floods and a regulatory floodway for each stream reach.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205011","collaboration":"Prepared in cooperation with Stark County and the Muskingum Watershed Conservancy District","usgsCitation":"Ostheimer, C.J. and Whitehead, M.T, 2020, Hydrologic and hydraulic analyses of selected streams in Stark County, Ohio: U.S. Geological Survey Scientific Investigations Report 2020–5011, 15 p., https://doi.org/10.3133/sir20205011.","productDescription":"Report: iv, 15 p.; 4 Appendixes; Data Release","numberOfPages":"24","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-106471","costCenters":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":399632,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109726.htm"},{"id":372523,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5011/coverthb.jpg"},{"id":372525,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2020/5011/sir20205011_appendix1.pdf","text":"Appendix 1","size":"3.09 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020–5011 Appendix 1","linkHelpText":"– Technical Support Data Notebook"},{"id":372526,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2020/5011/sir20205011_appendix2.pdf","text":"Appendix 2","size":"780 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020–5011 Appendix 2","linkHelpText":"– Floodway data tables"},{"id":372524,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5011/sir20205011.pdf","text":"Report","size":"1.25 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020–5011"},{"id":372527,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2020/5011/sir20205011_appendix3.pdf","text":"Appendix 3","size":"1.97 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020–5011 Appendix 3","linkHelpText":"– Water-surface profiles"},{"id":372528,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2020/5011/sir20205011_appendix4.pdf","text":"Appendix 4","size":"8.48 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020–5011 Appendix 4","linkHelpText":"– Flood-inundation maps"},{"id":372529,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9YQJ8B7","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Geospatial datasets and hydraulic models for selected streams in Stark County, Ohio"}],"country":"United States","state":"Ohio","county":"Stark County","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-81.0864,40.9879],[-81.0865,40.9839],[-81.0866,40.978],[-81.0869,40.9013],[-81.0873,40.728],[-81.0922,40.7285],[-81.1001,40.7281],[-81.1989,40.7292],[-81.1991,40.7224],[-81.2373,40.7237],[-81.241,40.6507],[-81.2755,40.651],[-81.2791,40.6511],[-81.304,40.6518],[-81.3173,40.6519],[-81.4372,40.6529],[-81.4365,40.6584],[-81.4395,40.6625],[-81.4467,40.6657],[-81.4589,40.6654],[-81.4675,40.6555],[-81.6489,40.6346],[-81.6491,40.6681],[-81.6483,40.7371],[-81.648,40.9145],[-81.4201,40.9064],[-81.4164,40.9889],[-81.3932,40.9887],[-81.1059,40.9882],[-81.0925,40.988],[-81.0864,40.9879]]]},\"properties\":{\"name\":\"Stark\",\"state\":\"OH\"}}]}","contact":"<p>Director, <a data-mce-href=\"https://www.usgs.gov/centers/oki-water\" href=\"https://www.usgs.gov/centers/oki-water\">Ohio-Kentucky-Indiana Water Science Center</a><br>U.S. Geological Survey<br>6460 Busch Boulevard Suite 100<br>Columbus, OH 43229–1737<br><br></p>","tableOfContents":"<ul><li>Abstract</li><li>Introduction</li><li>Study Approach</li><li>Hydrologic Analyses</li><li>Hydraulic Analyses</li><li>Development of Flood-Inundation Maps</li><li>Summary</li><li>References Cited</li><li>Appendixes 1–4</li></ul>","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"publishedDate":"2020-02-24","noUsgsAuthors":false,"publicationDate":"2020-02-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Ostheimer, Chad J. 0000-0002-4528-8867","orcid":"https://orcid.org/0000-0002-4528-8867","contributorId":213950,"corporation":false,"usgs":true,"family":"Ostheimer","given":"Chad","email":"","middleInitial":"J.","affiliations":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":781768,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Whitehead, Matthew T. 0000-0002-4888-2597 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,{"id":70208126,"text":"sir20205001 - 2020 - Modeling a 2- and 4-foot drawdown in the Link River to Keno Dam reach of the upper Klamath River, south-central Oregon","interactions":[],"lastModifiedDate":"2022-04-25T20:39:51.337234","indexId":"sir20205001","displayToPublicDate":"2020-02-24T12:23:19","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2020-5001","displayTitle":"Modeling a 2- and 4-Foot Drawdown in the Link River to Keno Dam Reach of the Upper Klamath River, South-Central Oregon","title":"Modeling a 2- and 4-foot drawdown in the Link River to Keno Dam reach of the upper Klamath River, south-central Oregon","docAbstract":"<h1>Executive Summary</h1><p class=\"p1\">The most upstream, pooled reach of the Klamath River in south-central Oregon, from Link River mouth to Keno Dam (Link-Keno), has a water-surface elevation that remains relatively constant throughout the year. Two model scenarios, using an existing two-dimensional hydrodynamic and water-quality model (CE-QUAL-W2), were constructed to examine the effects of lowering the water-surface elevation by 2 and 4 feet (ft) (0.61 and 1.2 meters) throughout an entire calendar year to mimic some of the potential effects of removal or modification of Keno Dam. Model results for these drawdown scenarios were analyzed for changes in velocity, travel time, water temperature, total dissolved solids, inorganic suspended sediment, nutrients, organic matter, chlorophyll <i>a</i>, and dissolved oxygen, compared to the base-case model. The model used in this study had been previously calibrated with the presence of aquatic plants (macrophytes). However, most model analyses were completed for model runs where macrophytes were “turned off” because the species, abundance, and distribution of macrophytes in a lowered-water scenario were all highly uncertain. For comparison, a few model scenario runs were completed with macrophytes enabled within the model. Findings from this study include the following:</p><ul><li>Modeled water velocity increased and travel time decreased substantially throughout the reach with the 2- and 4-ft drawdown scenarios, with travel time roughly halved in the 4-ft scenario under unchanged flow conditions.</li><li>For many water-quality constituents in the drawdown scenarios, the model showed little to no change in outflow concentrations at Keno Dam compared to the base case, which represents conditions based on year 2007 water-level elevations. However, chlorophyll <i>a </i>and particulate organic carbon concentrations increased in the Keno Dam outflow in summer with the drawdowns. This seemed to be related to the increased water velocity. As suspended algae and other particulate organic matter such as dead algal cells and detritus moved farther downstream with the faster velocity, there was relatively less deposition of that material in the most upstream model segments and relatively more deposition in downstream segments of the Link-Keno reach, especially in summer and autumn, the period with the largest algae bloom.</li><li>Despite minor differences in the Keno Dam outflow, modeled dissolved oxygen concentration and water temperature showed some changes in the Link-Keno reach compared to the base case, with differences as large as 2 milligrams per liter and 2 degrees Celsius, respectively, computed as segment averages and daily averages.</li><li>With macrophytes enabled, the model outflow in the drawdown scenarios showed a decrease in dissolved oxygen concentration in mid-summer that seemed to be related to decreased macrophyte abundance and primary production in those scenarios. The with-macrophyte model results have greater uncertainty, but the results indicated that macrophytes are likely to be an important factor in the dissolved oxygen budget under reduced water-surface elevations.</li></ul>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205001","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Sullivan, A.B., and Rounds, S.A., 2020, Modeling a 2- and 4-foot drawdown in the Link River to Keno Dam reach of the upper Klamath River, south-central Oregon: U.S. Geological Survey Scientific Investigations Report 2020–5001, 18 p., https://doi.org/10.3133/sir20205001.","productDescription":"vi, 18 p.","onlineOnly":"Y","ipdsId":"IP-110517","costCenters":[{"id":518,"text":"Oregon Water Science 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Science Center</a><br>U.S. Geological Survey<br>2130 SW 5th Avenue<br>Portland, Oregon 97201</p>","tableOfContents":"<ul><li>Executive Summary</li><li>Introduction</li><li>Methods</li><li>Results and Discussion</li><li>Acknowledgments</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"publishedDate":"2020-02-24","noUsgsAuthors":false,"publicationDate":"2020-02-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Sullivan, Annett B. 0000-0001-7783-3906 annett@usgs.gov","orcid":"https://orcid.org/0000-0001-7783-3906","contributorId":79821,"corporation":false,"usgs":true,"family":"Sullivan","given":"Annett B.","email":"annett@usgs.gov","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":false,"id":780621,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rounds, Stewart A. 0000-0002-8540-2206 sarounds@usgs.gov","orcid":"https://orcid.org/0000-0002-8540-2206","contributorId":905,"corporation":false,"usgs":true,"family":"Rounds","given":"Stewart","email":"sarounds@usgs.gov","middleInitial":"A.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":780622,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70210169,"text":"70210169 - 2020 - Runoff sensitivity to snow depletion curve representation within a continental scale hydrologic model","interactions":[],"lastModifiedDate":"2020-05-19T14:20:30.574872","indexId":"70210169","displayToPublicDate":"2020-02-24T09:15:24","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1924,"text":"Hydrological Processes","active":true,"publicationSubtype":{"id":10}},"title":"Runoff sensitivity to snow depletion curve representation within a continental scale hydrologic model","docAbstract":"The spatial variability of snow water equivalent (SWE) can exert a strong influence on the timing and magnitude of snowmelt delivery to a watershed. Therefore, the representation of subgrid or subwatershed snow variability in hydrologic models is important for accurately simulating snowmelt dynamics and runoff response. The U.S. Geological Survey National Hydrologic Model infrastructure with the Precipitation-Runoff Modeling System (NHM-PRMS) represents the subgrid variability of SWE with snow depletion curves (SDCs), which relate snow-covered area to watershed-average SWE during the snowmelt period. The main objective of this research was to evaluate the sensitivity of simulated runoff to SDC representation within the NHM-PRMS across the continental United States (CONUS). SDCs for the model experiment were derived assuming a range of SWE coefficient of variation (CV) values and a lognormal probability distribution function. The NHM-PRMS was simulated at a daily time step for each SDC over a 14-year period. Results highlight that increasing the subgrid snow variability (by changing the SDC) resulted in a consistently slower snowmelt rate and longer snowmelt duration when averaged across the hydrologic response unit scale. Simulated runoff was also found to be sensitive to SDC representation, as increases in the subgrid SWE CV by 1.0 resulted in decreases in runoff ratio by as much as 12 percent in snow-dominated regions of the CONUS. Simulated decreases in runoff associated with slower snowmelt rates were approximately inversely proportional to increases in simulated evapotranspiration. High snow persistence and peak SWE:annual precipitation combined with a water limited dryness index were associated with the greatest runoff sensitivity to changing snowmelt. Results from this study highlight the importance of carefully parameterizing SDCs for hydrologic modeling. Furthermore, improving model representation of snowmelt input variability and its relation to runoff generation processes is shown to be an important consideration for future modeling applications.","language":"English","publisher":"Wiley","doi":"10.1002/hyp.13735","usgsCitation":"Sexstone, G., Driscoll, J.M., Hay, L., Hammond, J., and Barnhart, T., 2020, Runoff sensitivity to snow depletion curve representation within a continental scale hydrologic model: Hydrological Processes, v. 34, no. 11, p. 2365-2380, https://doi.org/10.1002/hyp.13735.","productDescription":"16 p.","startPage":"2365","endPage":"2380","ipdsId":"IP-107421","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":437087,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9OEIRJF","text":"USGS data release","linkHelpText":"Data release in support of Runoff sensitivity to snow depletion curve representation within a continental scale 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]\n}","volume":"34","issue":"11","noUsgsAuthors":false,"publicationDate":"2020-03-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Sexstone, Graham A. 0000-0001-8913-0546","orcid":"https://orcid.org/0000-0001-8913-0546","contributorId":203850,"corporation":false,"usgs":true,"family":"Sexstone","given":"Graham A.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":789388,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Driscoll, Jessica M. 0000-0003-3097-9603 jdriscoll@usgs.gov","orcid":"https://orcid.org/0000-0003-3097-9603","contributorId":167585,"corporation":false,"usgs":true,"family":"Driscoll","given":"Jessica","email":"jdriscoll@usgs.gov","middleInitial":"M.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":789389,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hay, Lauren 0000-0003-3763-4595","orcid":"https://orcid.org/0000-0003-3763-4595","contributorId":205020,"corporation":false,"usgs":true,"family":"Hay","given":"Lauren","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":789390,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hammond, John C. 0000-0002-4935-0736","orcid":"https://orcid.org/0000-0002-4935-0736","contributorId":223108,"corporation":false,"usgs":true,"family":"Hammond","given":"John C.","affiliations":[{"id":41514,"text":"Maryland-Delaware-District of Columbia  Water Science Center","active":true,"usgs":true}],"preferred":true,"id":789391,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Barnhart, Theodore B. 0000-0002-9682-3217","orcid":"https://orcid.org/0000-0002-9682-3217","contributorId":202558,"corporation":false,"usgs":true,"family":"Barnhart","given":"Theodore B.","affiliations":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"preferred":true,"id":789392,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70208959,"text":"70208959 - 2020 - An experimental study of longitudinal incisional grooves in a mixed bedrock-alluvial channel","interactions":[],"lastModifiedDate":"2020-03-09T12:02:08","indexId":"70208959","displayToPublicDate":"2020-02-23T11:58:44","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":"An experimental study of longitudinal incisional grooves in a mixed bedrock-alluvial channel","docAbstract":"<p><span>Natural bedrock rivers have various bedforms created by erosion. Flow‐parallel incisional grooves formed longitudinally in bedrock are one common example of such bedforms. Although several studies have been conducted regarding these grooves, their formation processes are not well understood. In this study, we conducted a flume experiment to investigate the relationship between the flow structure and longitudinal grooves. The experimental results strongly suggest that longitudinal grooves are formed by moving sediment concentrated in multiple longitudinal pathways by turbulence‐driven secondary flows. The sediment preferentially abrades the bedrock along these flow‐parallel pathways resulting in longitudinal grooves in the bedrock. Measurements of the flow velocity distribution show that the positions of secondary flow cells producing the initial formation of the grooves are altered by the formation of those grooves. Because displaced secondary flows tend to make the sediment collide with the sidewalls of the longitudinal grooves, the grooves grow wider over time and some grooves partially combine with other adjacent grooves. The initial maximum number of longitudinal grooves&nbsp;</span><span><i>N</i><sub><i>max</i></sub></span><span>&nbsp;strongly depends on the river width‐depth ratio&nbsp;</span><span><i>B</i>/<i>D</i></span><span>, which defines the number of secondary flow cells, and can be expressed as&nbsp;</span><span><i>N</i><sub><i>max</i></sub>&nbsp;=&nbsp;0.5<i>B</i>/<i>D</i></span><span>. However, because some grooves coalesce with other grooves due to the effects of the displacement of secondary flows, the average number of grooves showed a relationship that can be expressed as&nbsp;</span><span><i>N</i>&nbsp;=&nbsp;0.41<i>B</i>/<i>D</i></span><span>. Based on this relationship, we inversely estimated the flow discharge of the Abashiri River using the number of longitudinal grooves observed in the river. The result was consistent with the observed annual maximum flow discharge of the river. This suggests that the number of longitudinal grooves can be used as an indicator for estimation of the formative flow discharge in bedrock rivers.</span></p>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2019WR025410","usgsCitation":"Inoue, T., and Nelson, J.M., 2020, An experimental study of longitudinal incisional grooves in a mixed bedrock-alluvial channel: Water Resources Research, v. 56, no. 3, e2019WR025410, 16 p., https://doi.org/10.1029/2019WR025410.","productDescription":"e2019WR025410, 16 p.","ipdsId":"IP-107443","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":487492,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2019wr025410","text":"Publisher Index Page"},{"id":373013,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"56","issue":"3","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2020-02-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Inoue, Takuya","contributorId":173794,"corporation":false,"usgs":false,"family":"Inoue","given":"Takuya","email":"","affiliations":[{"id":27295,"text":"Civil Engineering Research Institute, Sapporo, Japan","active":true,"usgs":false}],"preferred":false,"id":784200,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nelson, Jonathan M. 0000-0002-7632-8526 jmn@usgs.gov","orcid":"https://orcid.org/0000-0002-7632-8526","contributorId":2812,"corporation":false,"usgs":true,"family":"Nelson","given":"Jonathan","email":"jmn@usgs.gov","middleInitial":"M.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":784199,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70209088,"text":"70209088 - 2020 - Long term persistence of aspen in snowdrift-dependent ecosystems","interactions":[],"lastModifiedDate":"2020-03-15T13:48:16","indexId":"70209088","displayToPublicDate":"2020-02-22T13:47:11","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1687,"text":"Forest Ecology and Management","active":true,"publicationSubtype":{"id":10}},"title":"Long term persistence of aspen in snowdrift-dependent ecosystems","docAbstract":"Quaking aspen (Populus tremuloides) forests throughout the western United States have\nexperienced significant mortality in recent decades, much of which has been influenced by\nclimate variability, especially drought. In the western portion of its range, where most\tprecipitation arrives during winter as snowfall and summers are dry, snowdrifts that persist into\tthe growing season provide soil moisture recharge that sustain many aspen groves that are\timportant locations of biodiversity within the landscape. There is growing concern that reduced\nsnowpack due to climate change may reduce the long-term persistence and productivity of aspen communities in these regions. In this study, we evaluated the potential for climate change and\tdrought to reduce or eliminate isolated aspen communities in southwestern Idaho. We used a landscape simulation model integrated with inputs from an empirically derived biogeochemical\nmodel of growth, and a species distribution model of regeneration to forecast how changes in\nclimate, declining snowpack, and competition with a conifer species is likely to affect aspen\noccupancy over the next 85-years. We found that simulated reductions in snowpack depth (and\nassociated increases in climatic water deficit) caused a reduction in aspen persistence; aspen\noccupancy was reduced under all high emissions climate scenarios. Douglas-fir (Pseudotsuga\nmenziesii) occupancy also declined under all future climates. Aspen regeneration declined over\nthe course of all simulations, with an ensemble ratio of mortality/establishment increasing over\nthe course of both low and high emissions climate scenarios. Climate-induced mortality of aspen\nclones increased in frequency under all climate scenarios and, under the most severe emissions\nscenarios, contributed to a substantial decline of aspen cover. Our research suggests that\nsnowbanks will be an important determinant of long-term persistence of aspen under changing climate in the region.","language":"English","publisher":"Elseiver","doi":"10.1016/j.foreco.2020.118005","usgsCitation":"Kretchun, A.M., Scheller, R., Shinneman, D.J., Soderquist, B., Maguire, K.C., Link, T., and Strand, E.K., 2020, Long term persistence of aspen in snowdrift-dependent ecosystems: Forest Ecology and Management, v. 462, 118005, https://doi.org/10.1016/j.foreco.2020.118005.","productDescription":"118005","ipdsId":"IP-112095","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":457627,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.foreco.2020.118005","text":"Publisher Index Page"},{"id":373273,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"462","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Kretchun, Alec M","contributorId":223372,"corporation":false,"usgs":false,"family":"Kretchun","given":"Alec","email":"","middleInitial":"M","affiliations":[{"id":40703,"text":"Quantum Spatial","active":true,"usgs":false}],"preferred":false,"id":784879,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Scheller, Robert M","contributorId":147807,"corporation":false,"usgs":false,"family":"Scheller","given":"Robert M","affiliations":[{"id":16941,"text":"Environmental Science and Management Department, Portland State University","active":true,"usgs":false}],"preferred":false,"id":784880,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shinneman, Douglas J. 0000-0002-4909-5181 dshinneman@usgs.gov","orcid":"https://orcid.org/0000-0002-4909-5181","contributorId":147745,"corporation":false,"usgs":true,"family":"Shinneman","given":"Douglas","email":"dshinneman@usgs.gov","middleInitial":"J.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":784878,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Soderquist, B","contributorId":223373,"corporation":false,"usgs":false,"family":"Soderquist","given":"B","email":"","affiliations":[{"id":37389,"text":"U.S. Forest Service","active":true,"usgs":false}],"preferred":false,"id":784882,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Maguire, Kaitlin C. 0000-0001-8193-2384","orcid":"https://orcid.org/0000-0001-8193-2384","contributorId":203419,"corporation":false,"usgs":true,"family":"Maguire","given":"Kaitlin","email":"","middleInitial":"C.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":784881,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Link, Timothy E","contributorId":223374,"corporation":false,"usgs":false,"family":"Link","given":"Timothy E","affiliations":[{"id":36394,"text":"University of Idaho","active":true,"usgs":false}],"preferred":false,"id":784883,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Strand, Eva K.","contributorId":149810,"corporation":false,"usgs":false,"family":"Strand","given":"Eva","email":"","middleInitial":"K.","affiliations":[{"id":17832,"text":"University of Idaho Department of Forest, Rangeland, and Fire Sciences","active":true,"usgs":false}],"preferred":false,"id":784884,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70208644,"text":"70208644 - 2020 - Characterizing land surface phenology and exotic annual grasses in dryland ecosystems using Landsat and Sentinel-2 data in harmony","interactions":[],"lastModifiedDate":"2022-03-31T18:52:42.924432","indexId":"70208644","displayToPublicDate":"2020-02-22T06:42:15","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Characterizing land surface phenology and exotic annual grasses in dryland ecosystems using Landsat and Sentinel-2 data in harmony","docAbstract":"Invasive annual grasses, such as cheatgrass (Bromus tectorum L.), have proliferated in dryland ecosystems of the western United States, promoting increased fire activity and reduced biodiversity that can be detrimental to socio-environmental systems. Monitoring exotic annual grass cover and dynamics over large areas requires the use of remote sensing that can support early detection and rapid response initiatives. However, few studies have leveraged remote sensing technologies and computing frameworks capable of providing rangeland managers with maps of exotic annual grass cover at relatively high spatiotemporal resolutions and near real-time latencies. Here, we developed a system for automated mapping of invasive annual grass (%) cover using in situ observations, harmonized Landsat and Sentinel-2 (HLS) data, maps of biophysical variables, and machine learning techniques. A robust and automated cloud, cloud shadow, water, and snow/ice masking procedure (mean overall accuracy >81%) was implemented using time-series outlier detection and data mining techniques prior to spatiotemporal interpolation of HLS data via regression tree models (r = 0.94; mean absolute error (MAE) = 0.02). Weekly, cloud-free normalized difference vegetation index (NDVI) image composites (2016–2018) were used to construct a suite of spectral and phenological metrics (e.g., start and end of season dates), consistent with information derived from Moderate Resolution Image Spectroradiometer (MODIS) data. These metrics were incorporated into a data mining framework that accurately (r = 0.83; MAE = 11) modeled and mapped exotic annual grass (%) cover throughout dryland ecosystems in the western United States at a native, 30-m spatial resolution. Our results show that inclusion of weekly HLS time-series data and derived indicators improves our ability to map exotic annual grass cover, as compared to distribution models that use MODIS products or monthly, seasonal, or annual HLS composites as primary inputs. This research fills a critical gap in our ability to effectively assess, manage, and monitor drylands by providing a framework that allows for an accurate and timely depiction of land surface phenology and exotic annual grass cover at spatial and temporal resolutions that are meaningful to local resource managers.","language":"English","publisher":"MDPI","doi":"10.3390/rs12040725","usgsCitation":"Pastick, N., Dahal, D., Wylie, B.K., Parajuli, S., Boyte, S.P., and Wu, Z., 2020, Characterizing land surface phenology and exotic annual grasses in dryland ecosystems using Landsat and Sentinel-2 data in harmony: Remote Sensing, v. 12, no. 4, 725, 17 p.; Data release, https://doi.org/10.3390/rs12040725.","productDescription":"725, 17 p.; Data release","ipdsId":"IP-114798","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":457631,"rank":4,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs12040725","text":"Publisher Index Page"},{"id":437093,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P91NJ2PD","text":"USGS data release","linkHelpText":"Near real time estimation of annual exotic herbaceous fractional cover in the sagebrush ecosystem 30m, USA, July 2020"},{"id":437092,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9KKPT07","text":"USGS data release","linkHelpText":"Weekly cloud free Harmonized Landsat Sentinel-2 (HLS) Normalized Difference Vegetation Index (NDVI) data for western United States (2016 &amp;amp;amp;ndash; 2019)."},{"id":437091,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9XT1BV2","text":"USGS data release","linkHelpText":"Fractional estimates of exotic annual grass cover in dryland ecosystems of western United States (2016 - 2019)"},{"id":372534,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":397944,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9ZZSX5Q","text":"USGS data release","description":"USGS data release","linkHelpText":"Early estimates of Annual Exotic Herbaceous Fractional Cover in the Sagebrush Ecosystem, USA, May 2020"}],"country":"United States","state":"California, Idaho, Nevada, Oregon","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -121.728515625,\n              40.97989806962013\n            ],\n            [\n              -114.7412109375,\n              40.97989806962013\n            ],\n            [\n              -114.7412109375,\n              44.18220395771566\n            ],\n            [\n              -121.728515625,\n              44.18220395771566\n            ],\n            [\n              -121.728515625,\n              40.97989806962013\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"12","issue":"4","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2020-02-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Pastick, Neal 0000-0002-4321-6739","orcid":"https://orcid.org/0000-0002-4321-6739","contributorId":222683,"corporation":false,"usgs":true,"family":"Pastick","given":"Neal","email":"","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":false,"id":782880,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dahal, Devendra 0000-0001-9594-1249 ddahal@usgs.gov","orcid":"https://orcid.org/0000-0001-9594-1249","contributorId":5622,"corporation":false,"usgs":true,"family":"Dahal","given":"Devendra","email":"ddahal@usgs.gov","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":782883,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wylie, Bruce K. 0000-0002-7374-1083 wylie@usgs.gov","orcid":"https://orcid.org/0000-0002-7374-1083","contributorId":750,"corporation":false,"usgs":true,"family":"Wylie","given":"Bruce","email":"wylie@usgs.gov","middleInitial":"K.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":782881,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Parajuli, Sujan 0000-0002-1652-3063","orcid":"https://orcid.org/0000-0002-1652-3063","contributorId":222684,"corporation":false,"usgs":true,"family":"Parajuli","given":"Sujan","email":"","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":782882,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Boyte, Stephen P. 0000-0002-5462-3225 sboyte@usgs.gov","orcid":"https://orcid.org/0000-0002-5462-3225","contributorId":139238,"corporation":false,"usgs":true,"family":"Boyte","given":"Stephen","email":"sboyte@usgs.gov","middleInitial":"P.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":782884,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wu, Zhuoting 0000-0001-7393-1832 zwu@usgs.gov","orcid":"https://orcid.org/0000-0001-7393-1832","contributorId":4953,"corporation":false,"usgs":true,"family":"Wu","given":"Zhuoting","email":"zwu@usgs.gov","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true},{"id":498,"text":"Office of Land Remote Sensing (Geography)","active":true,"usgs":true}],"preferred":true,"id":782885,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70209323,"text":"70209323 - 2020 - The NASA hydrological forecast system for food and water security applications","interactions":[],"lastModifiedDate":"2020-08-05T13:51:35.378688","indexId":"70209323","displayToPublicDate":"2020-02-21T16:42:12","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1112,"text":"Bulletin of the American Meteorological Society","onlineIssn":"1520-0477","printIssn":"0003-0007","active":true,"publicationSubtype":{"id":10}},"title":"The NASA hydrological forecast system for food and water security applications","docAbstract":"Many regions in Africa and the Middle East are vulnerable to drought and to water and food insecurity, motivating agency efforts such as the U.S. Agency for International Development’s (USAID) Famine Early Warning System Network (FEWS NET) to provide early warning of drought events in the region. Each year these warnings guide life-saving assistance that reaches millions of people. A new NASA multi-model, remote sensing-based hydrological forecasting and analysis system, NHyFAS, has been developed to support such efforts by improving the FEWS NET’s current early warning capabilities. NHyFAS derives its skill from two sources: (i) accurate initial conditions, as produced by an offline land modeling system through the application and/or assimilation of various satellite data (precipitation, soil moisture, and terrestrial water storage); and (ii) meteorological forcing data during the forecast period as produced by a state-of-the-art ocean-land-atmosphere forecast system. The land modeling framework used is the Land Information System (LIS), which employs a suite of land surface models, allowing multi-model ensembles and multiple data assimilation strategies to better estimate land surface conditions. An evaluation of NHyFAS shows that its one-to-five month forecasts successfully capture known historic drought events. The system also benefits from strong collaboration with end-user partners in Africa and the Middle East, who provide insights on strategies to formulate and communicate early warning indicators to water and food security communities. The additional lead time provided by this system will increase the speed, accuracy and efficacy of humanitarian disaster relief, helping to save lives and livelihoods.","language":"English","publisher":"American Meteorological Society","doi":"10.1175/BAMS-D-18-0264.1","usgsCitation":"Arsenault, K., Shukla, S., Hazra, A., Getirana, A., McNally, A., Kumar, S., Koster, R., Peters-Lidard, C., Zaitchik, B., Badr, H., Jung, H.C., Narapusetty, B., , N., Wang, S., Mocko, D.M., Funk, C., Harrison, L., Husak, G.J., Adoum, A., Galu, G., Magadzire, T., Roningen, J., Shaw, M.J., Eylander, J., Bergaoui, K., McDonnell, R.A., and Verdin, J., 2020, The NASA hydrological forecast system for food and water security applications: Bulletin of the American Meteorological Society, v. 101, no. 7, p. E1007-E1025, https://doi.org/10.1175/BAMS-D-18-0264.1.","productDescription":"19 p.","startPage":"E1007","endPage":"E1025","ipdsId":"IP-117242","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":457635,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1175/bams-d-18-0264.1","text":"Publisher Index Page"},{"id":373697,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Africa, Middle East","volume":"101","issue":"7","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Arsenault, Kristi","contributorId":198836,"corporation":false,"usgs":false,"family":"Arsenault","given":"Kristi","affiliations":[],"preferred":false,"id":786063,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shukla, Shraddhanand","contributorId":145841,"corporation":false,"usgs":false,"family":"Shukla","given":"Shraddhanand","affiliations":[{"id":16255,"text":"Climate Hazards Group University of California Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":786064,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hazra, Abheera","contributorId":223718,"corporation":false,"usgs":false,"family":"Hazra","given":"Abheera","email":"","affiliations":[{"id":39055,"text":"NASA GSFC","active":true,"usgs":false}],"preferred":false,"id":786065,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Getirana, Agusto","contributorId":223719,"corporation":false,"usgs":false,"family":"Getirana","given":"Agusto","affiliations":[{"id":39055,"text":"NASA GSFC","active":true,"usgs":false}],"preferred":false,"id":786066,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McNally, Amy","contributorId":145810,"corporation":false,"usgs":false,"family":"McNally","given":"Amy","email":"","affiliations":[{"id":16236,"text":"UCSB Climate Hazards Group","active":true,"usgs":false}],"preferred":false,"id":786067,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kumar, Sujay","contributorId":198837,"corporation":false,"usgs":false,"family":"Kumar","given":"Sujay","email":"","affiliations":[],"preferred":false,"id":786068,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Koster, Randal","contributorId":223720,"corporation":false,"usgs":false,"family":"Koster","given":"Randal","email":"","affiliations":[{"id":39055,"text":"NASA GSFC","active":true,"usgs":false}],"preferred":false,"id":786069,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Peters-Lidard, Christa","contributorId":198839,"corporation":false,"usgs":false,"family":"Peters-Lidard","given":"Christa","email":"","affiliations":[],"preferred":false,"id":786070,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Zaitchik, Ben","contributorId":223721,"corporation":false,"usgs":false,"family":"Zaitchik","given":"Ben","email":"","affiliations":[{"id":37540,"text":"John Hopkins University","active":true,"usgs":false}],"preferred":false,"id":786071,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Badr, Hamada","contributorId":223722,"corporation":false,"usgs":false,"family":"Badr","given":"Hamada","email":"","affiliations":[{"id":37540,"text":"John Hopkins University","active":true,"usgs":false}],"preferred":false,"id":786072,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Jung, Hahn Chul","contributorId":223742,"corporation":false,"usgs":false,"family":"Jung","given":"Hahn","email":"","middleInitial":"Chul","affiliations":[],"preferred":false,"id":786155,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Narapusetty, Bala","contributorId":223743,"corporation":false,"usgs":false,"family":"Narapusetty","given":"Bala","email":"","affiliations":[],"preferred":false,"id":786156,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":" Navari","contributorId":223744,"corporation":false,"usgs":false,"given":"Navari","email":"","affiliations":[],"preferred":false,"id":786157,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Wang, Shugong","contributorId":198838,"corporation":false,"usgs":false,"family":"Wang","given":"Shugong","email":"","affiliations":[],"preferred":false,"id":786158,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Mocko, David M.","contributorId":223745,"corporation":false,"usgs":false,"family":"Mocko","given":"David","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":786159,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Funk, Chris 0000-0002-9254-6718 cfunk@usgs.gov","orcid":"https://orcid.org/0000-0002-9254-6718","contributorId":167070,"corporation":false,"usgs":true,"family":"Funk","given":"Chris","email":"cfunk@usgs.gov","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":786160,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Harrison, Laura","contributorId":192382,"corporation":false,"usgs":false,"family":"Harrison","given":"Laura","email":"","affiliations":[],"preferred":false,"id":786161,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Husak, Gregory J.","contributorId":34435,"corporation":false,"usgs":true,"family":"Husak","given":"Gregory","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":786162,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Adoum, Alkhalil","contributorId":59670,"corporation":false,"usgs":true,"family":"Adoum","given":"Alkhalil","email":"","affiliations":[],"preferred":false,"id":786163,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Galu, Gideon","contributorId":97360,"corporation":false,"usgs":true,"family":"Galu","given":"Gideon","affiliations":[],"preferred":false,"id":786164,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Magadzire, Tamuka","contributorId":145822,"corporation":false,"usgs":false,"family":"Magadzire","given":"Tamuka","affiliations":[{"id":16236,"text":"UCSB Climate Hazards Group","active":true,"usgs":false}],"preferred":false,"id":786165,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Roningen, Jeanne","contributorId":223746,"corporation":false,"usgs":false,"family":"Roningen","given":"Jeanne","email":"","affiliations":[],"preferred":false,"id":786166,"contributorType":{"id":1,"text":"Authors"},"rank":22},{"text":"Shaw, Michael J.","contributorId":28514,"corporation":false,"usgs":true,"family":"Shaw","given":"Michael","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":786167,"contributorType":{"id":1,"text":"Authors"},"rank":23},{"text":"Eylander, John","contributorId":210915,"corporation":false,"usgs":false,"family":"Eylander","given":"John","email":"","affiliations":[{"id":13502,"text":"US Army Corps of Engineers","active":true,"usgs":false}],"preferred":false,"id":786168,"contributorType":{"id":1,"text":"Authors"},"rank":24},{"text":"Bergaoui, Karim","contributorId":223747,"corporation":false,"usgs":false,"family":"Bergaoui","given":"Karim","email":"","affiliations":[],"preferred":false,"id":786169,"contributorType":{"id":1,"text":"Authors"},"rank":25},{"text":"McDonnell, Rachael A.","contributorId":223748,"corporation":false,"usgs":false,"family":"McDonnell","given":"Rachael","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":786170,"contributorType":{"id":1,"text":"Authors"},"rank":26},{"text":"Verdin, James 0000-0003-0238-9657 verdin@usgs.gov","orcid":"https://orcid.org/0000-0003-0238-9657","contributorId":145830,"corporation":false,"usgs":true,"family":"Verdin","given":"James","email":"verdin@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":786171,"contributorType":{"id":1,"text":"Authors"},"rank":27}]}}
,{"id":70208590,"text":"sir20195142 - 2020 - Assessment of soil and water resources in the Organ Mountains-Desert Peaks National Monument, New Mexico","interactions":[],"lastModifiedDate":"2022-04-25T20:20:35.352401","indexId":"sir20195142","displayToPublicDate":"2020-02-21T13:52:10","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2019-5142","displayTitle":"Assessment of Soil and Water Resources in the Organ Mountains-Desert Peaks National Monument, New Mexico","title":"Assessment of soil and water resources in the Organ Mountains-Desert Peaks National Monument, New Mexico","docAbstract":"<p>The Organ Mountains-Desert Peaks National Monument (Monument) in southern New Mexico was established in 2014. Given anticipated future demands in the Monument for recreation, livestock grazing, and maintenance of rights-of-way (for example, pipelines and powerlines), the Bureau of Land Management (BLM) needs a better understanding of the current soil and water resources and how infrastructure improvements could affect these resources and the watershed. Specifically, the BLM is concerned with infiltration and erosion and their relations to existing or planned infrastructure, such as roads, campgrounds, location of livestock grazing, and rights-of-way. Alternatives to the current land-use conditions, land-management practices, and infrastructure will be assessed by BLM to best protect Monument resources. The U.S. Geological Survey, in cooperation with the BLM, conducted a study to assess the soil and water resources within the Monument to provide an inventory and compilation of natural-resource information needed by resource managers for the BLM’s land-use planning process for this new national monument. The overall objectives of this study were to (1) compile and interpret existing soil- and water-resource data for the Monument and (2) provide a basic assessment of the surface hydrological effects of selected alternatives to current land use and infrastructure. Data were compiled by using geographic information system software and evaluated for hydrologic and landscape properties that influence infiltration, runoff, and erosion. The effects of changing vegetation were simulated by using different scenarios in the Rangeland Hydrology and Erosion Model. Results of this model indicate areas where soil loss or runoff may occur.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195142","collaboration":"Prepared in cooperation with the Bureau of Land Management","usgsCitation":"Blake, J.M., Mitchell, A.C., Shephard, Z., Ball, G., Chavarria, S., and Douglas-Mankin, K.R., 2020, Assessment of soil and water resources in the Organ Mountains-Desert Peaks National Monument, New Mexico: U.S. Geological Survey Scientific Investigations Report 2019–5142, 64 p., https://doi.org/10.3133/sir20195142.","productDescription":"Report: x, 64 p.; Data Release","numberOfPages":"78","onlineOnly":"Y","ipdsId":"IP-098054","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":372464,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5142/sir20195142.pdf","text":"Report","size":"87.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019–5142"},{"id":399617,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109724.htm"},{"id":372465,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9JVHA4Z","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Database associated with the assessment of soil and water resources in the Organ Mountains-Desert Peaks National Monument"},{"id":372463,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5142/coverthb.jpg"}],"country":"United States","state":"New Mexico","otherGeospatial":"Organ Mountains-Desert Peaks National Monument","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -107.3,\n              31.8511\n            ],\n            [\n              -106.4639,\n              31.8511\n            ],\n            [\n              -106.4639,\n              32.6628\n            ],\n            [\n              -107.3,\n              32.6628\n            ],\n            [\n              -107.3,\n              31.8511\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p>Director, <a data-mce-href=\"https://www.usgs.gov/centers/nm-water/\" href=\"https://www.usgs.gov/centers/nm-water/\">New Mexico Water Science Center</a><br>U.S. Geological Survey<br>6700 Edith Blvd NE<br>Albuquerque, New Mexico 87113<br></p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Study Area Description and Background</li><li>Methods</li><li>Assessment of Soil and Water Resources</li><li>Data Gaps Identified and Further Study Needs</li><li>Summary</li><li>References</li></ul>","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"publishedDate":"2020-02-21","noUsgsAuthors":false,"publicationDate":"2020-02-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Blake, Johanna M. 0000-0003-4667-0096","orcid":"https://orcid.org/0000-0003-4667-0096","contributorId":211907,"corporation":false,"usgs":true,"family":"Blake","given":"Johanna M.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":782632,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mitchell, Aurelia C. 0000-0003-3302-4546","orcid":"https://orcid.org/0000-0003-3302-4546","contributorId":222580,"corporation":false,"usgs":true,"family":"Mitchell","given":"Aurelia C.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":782635,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shephard, Zachary M. 0000-0003-2994-3355","orcid":"https://orcid.org/0000-0003-2994-3355","contributorId":222581,"corporation":false,"usgs":true,"family":"Shephard","given":"Zachary","email":"","middleInitial":"M.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":782636,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ball, Grady 0000-0003-3030-055X","orcid":"https://orcid.org/0000-0003-3030-055X","contributorId":222582,"corporation":false,"usgs":true,"family":"Ball","given":"Grady","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":782637,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Chavarria, Shaleene 0000-0001-8792-1010","orcid":"https://orcid.org/0000-0001-8792-1010","contributorId":222578,"corporation":false,"usgs":true,"family":"Chavarria","given":"Shaleene","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":782633,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Douglas-Mankin, Kyle R. 0000-0002-3155-3666","orcid":"https://orcid.org/0000-0002-3155-3666","contributorId":222579,"corporation":false,"usgs":false,"family":"Douglas-Mankin","given":"Kyle R.","affiliations":[{"id":40563,"text":"Former NMWSC","active":true,"usgs":false}],"preferred":false,"id":782634,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70210221,"text":"70210221 - 2020 - A call for global action to conserve native trout in the 21st century and beyond","interactions":[],"lastModifiedDate":"2020-07-09T15:01:41.623945","indexId":"70210221","displayToPublicDate":"2020-02-21T08:15:55","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1471,"text":"Ecology of Freshwater Fish","active":true,"publicationSubtype":{"id":10}},"title":"A call for global action to conserve native trout in the 21st century and beyond","docAbstract":"<p>Trout and char (hereafter,<span>&nbsp;</span><i>trout<span>&nbsp;</span></i>) represent some of the more culturally, economically and ecologically important taxa of freshwater fishes worldwide (Kershner, Williams, Gresswell, &amp; Lobón‐Cerviá,<span>&nbsp;</span><span>2019a</span>). Native to all continents in the Northern Hemisphere (as well as western Mediterranean Africa), trout belong to seven genera (<i>Oncorhynchus<span>&nbsp;</span></i>,<span>&nbsp;</span><i>Salvelinus, Salmo<span>&nbsp;</span></i>,<span>&nbsp;</span><i>Hucho, Parahucho, Brachymystax<span>&nbsp;</span></i>and<span>&nbsp;</span><i>Salvethymus<span>&nbsp;</span></i>), which are distributed across more than 60 countries (Muhlfeld et al.,<span>&nbsp;</span><span>2019</span>). Despite their broad importance as indicators of biodiversity in cold‐water ecosystems (Haak &amp; Williams,<span>&nbsp;</span><span>2013</span>), as well as cultural icons for food and recreation, nearly half of the world's recognised trout species (IUCN,<span>&nbsp;</span><span>2018</span>) are imperilled or at risk of global extinction (Muhlfeld et al.,<span>&nbsp;</span><span>2018</span>,<span>&nbsp;</span><span>2019</span>). The root causes of their vulnerability include broad‐scale alteration of landscapes and watersheds, dams, overharvest, pollution, interactions with hatchery‐bred conspecifics and non‐native species. However, emerging threats such as climate change and related problems such as the spread of diseases and parasites pose significant challenges and uncertainties to native trout and their habitats (Kovach et al.,<span>&nbsp;</span><span>2016</span>; Muhlfeld et al.,<span>&nbsp;</span><span>2018</span>). Ultimately, conservation of native trout depends on understanding their diversity, a willingness to address threats at their root causes and implementing progressive conservation solutions that promote persistence of these iconic species in the face of growing human pressures.</p>","language":"English","publisher":"Wiley","doi":"10.1111/eff.12538","usgsCitation":"Dauwalter, D.C., Duchi, A., Epifanio, J., Gandolfi, A., Gresswell, R.E., Juanes, F., Kershner, J.L., Lobon-Cervia, J., McGinnity, P., Meraner, A., Mikheev, P., Morita, K., Muhlfeld, C.C., Pinter, K., Post, J., Unfer, G., Vøllestad, L., and Williams, J.E., 2020, A call for global action to conserve native trout in the 21st century and beyond: Ecology of Freshwater Fish, v. 29, no. 3, p. 429-432, https://doi.org/10.1111/eff.12538.","productDescription":"4 p.","startPage":"429","endPage":"432","ipdsId":"IP-111833","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":374994,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"29","issue":"3","noUsgsAuthors":false,"publicationDate":"2020-02-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Dauwalter, Daniel C.","contributorId":69879,"corporation":false,"usgs":true,"family":"Dauwalter","given":"Daniel","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":789602,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Duchi, Antonino","contributorId":224805,"corporation":false,"usgs":false,"family":"Duchi","given":"Antonino","email":"","affiliations":[],"preferred":false,"id":789603,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Epifanio, John","contributorId":139202,"corporation":false,"usgs":false,"family":"Epifanio","given":"John","email":"","affiliations":[],"preferred":false,"id":789604,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gandolfi, A.J.","contributorId":58843,"corporation":false,"usgs":true,"family":"Gandolfi","given":"A.J.","email":"","affiliations":[],"preferred":false,"id":789605,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gresswell, Robert E. 0000-0003-0063-855X bgresswell@usgs.gov","orcid":"https://orcid.org/0000-0003-0063-855X","contributorId":152031,"corporation":false,"usgs":true,"family":"Gresswell","given":"Robert","email":"bgresswell@usgs.gov","middleInitial":"E.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":789606,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Juanes, Francis","contributorId":224807,"corporation":false,"usgs":false,"family":"Juanes","given":"Francis","email":"","affiliations":[],"preferred":false,"id":789607,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kershner, Jeffrey L. 0000-0002-7093-9860 jkershner@usgs.gov","orcid":"https://orcid.org/0000-0002-7093-9860","contributorId":310,"corporation":false,"usgs":true,"family":"Kershner","given":"Jeffrey","email":"jkershner@usgs.gov","middleInitial":"L.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":789608,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Lobon-Cervia, Javier","contributorId":69052,"corporation":false,"usgs":true,"family":"Lobon-Cervia","given":"Javier","email":"","affiliations":[],"preferred":false,"id":789609,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"McGinnity, Philip","contributorId":224809,"corporation":false,"usgs":false,"family":"McGinnity","given":"Philip","email":"","affiliations":[],"preferred":false,"id":789610,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Meraner, Andreas","contributorId":224810,"corporation":false,"usgs":false,"family":"Meraner","given":"Andreas","email":"","affiliations":[],"preferred":false,"id":789611,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Mikheev, Pavel","contributorId":224811,"corporation":false,"usgs":false,"family":"Mikheev","given":"Pavel","email":"","affiliations":[],"preferred":false,"id":789612,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Morita, Kentaro","contributorId":224812,"corporation":false,"usgs":false,"family":"Morita","given":"Kentaro","email":"","affiliations":[],"preferred":false,"id":789613,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Muhlfeld, Clint C. 0000-0002-4599-4059 cmuhlfeld@usgs.gov","orcid":"https://orcid.org/0000-0002-4599-4059","contributorId":924,"corporation":false,"usgs":true,"family":"Muhlfeld","given":"Clint","email":"cmuhlfeld@usgs.gov","middleInitial":"C.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":789614,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Pinter, Kurt","contributorId":224813,"corporation":false,"usgs":false,"family":"Pinter","given":"Kurt","email":"","affiliations":[],"preferred":false,"id":789615,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Post, John","contributorId":224814,"corporation":false,"usgs":false,"family":"Post","given":"John","email":"","affiliations":[],"preferred":false,"id":789616,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Unfer, Gunther","contributorId":224815,"corporation":false,"usgs":false,"family":"Unfer","given":"Gunther","email":"","affiliations":[],"preferred":false,"id":789617,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Vøllestad, Leif Asbjørn","contributorId":224828,"corporation":false,"usgs":false,"family":"Vøllestad","given":"Leif Asbjørn","affiliations":[],"preferred":false,"id":789664,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Williams, Jack E.","contributorId":93774,"corporation":false,"usgs":true,"family":"Williams","given":"Jack","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":789665,"contributorType":{"id":1,"text":"Authors"},"rank":18}]}}
,{"id":70208833,"text":"70208833 - 2020 - Broad-scale impacts of an invasive native predator on a sensitive native prey species within the shifting avian community of the North American Great Basin","interactions":[],"lastModifiedDate":"2020-03-03T08:16:45","indexId":"70208833","displayToPublicDate":"2020-02-21T08:12:51","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":"Broad-scale impacts of an invasive native predator on a sensitive native prey species within the shifting avian community of the North American Great Basin","docAbstract":"Human enterprise has modified ecosystem processes through direct and indirect alteration of native predators’ distribution and abundance. For example, human activities subsidize food, water, and shelter availability to generalist predators whose subsequent increased abundance impacts lower trophic-level prey species. The common raven (Corvus corax; hereafter, raven) is an avian predator, native to the northern hemisphere, that can become invasive when subsidized. Raven populations are increasing at unprecedented rates in many regions globally. Information regarding scale of impact and potential ecological thresholds is needed to guide conservation actions aimed at reducing adverse effects on sensitive prey. We conducted a multi-part analysis to investigate broad-scale variation in raven densities and impacts on nesting greater sage-grouse (Centrocercus urophasianus), an indicator species for sagebrush ecosystems in western North America. We estimated raven densities using 16,000 point surveys over 10 years within the Great Basin, USA, and examined associations with anthropogenic and environmental covariates. Average density was 0.54 ravens km-2 (95% CI: 0.42–0.70), with higher densities at lower relative elevations comprising increased agriculture and development. We then used a reduced dataset to estimate the effect of raven density on sage-grouse nest survival (nests = 737). We identified negative impacts to nesting sage-grouse, especially where raven density exceeded ~ 0.40 km-2, a potential ecological threshold. We mapped regions where elevated raven densities were predicted to depress sage-grouse population growth in the absence of compensatory demographic responses from other sage-grouse life-history stages, and found ~ 64% of sage-grouse breeding areas were adversely impacted by high raven density.","language":"English","publisher":"Elsevier","doi":"10.1016/j.biocon.2020.108409","usgsCitation":"Coates, P.S., O'Neil, S., Brussee, B.E., Ricca, M.A., Jackson, P.J., Dinkins, J.B., Howe, K., Moser, A.M., Foster, L.J., and Delahunty, D.J., 2020, Broad-scale impacts of an invasive native predator on a sensitive native prey species within the shifting avian community of the North American Great Basin: Biological Conservation, v. 243, 108409, 10 p., https://doi.org/10.1016/j.biocon.2020.108409.","productDescription":"108409, 10 p.","ipdsId":"IP-112833","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":437097,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9PULSDK","text":"USGS data release","linkHelpText":"raventools v1.0"},{"id":437096,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9T5JT8N","text":"USGS data release","linkHelpText":"Data maps of predicted raven density and areas of potential impact to nesting sage-grouse within sagebrush ecosystems of the North American Great Basin"},{"id":372833,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Idaho, Nevada, Oregon, Utah","otherGeospatial":"Great Basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              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pcoates@usgs.gov","orcid":"https://orcid.org/0000-0003-2672-9994","contributorId":3263,"corporation":false,"usgs":true,"family":"Coates","given":"Peter","email":"pcoates@usgs.gov","middleInitial":"S.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":783548,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"O'Neil, Shawn","contributorId":222928,"corporation":false,"usgs":true,"family":"O'Neil","given":"Shawn","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":783549,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brussee, Brianne E. 0000-0002-2452-7101 bbrussee@usgs.gov","orcid":"https://orcid.org/0000-0002-2452-7101","contributorId":4249,"corporation":false,"usgs":true,"family":"Brussee","given":"Brianne","email":"bbrussee@usgs.gov","middleInitial":"E.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":783550,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ricca, Mark A. 0000-0003-1576-513X mark_ricca@usgs.gov","orcid":"https://orcid.org/0000-0003-1576-513X","contributorId":139103,"corporation":false,"usgs":true,"family":"Ricca","given":"Mark","email":"mark_ricca@usgs.gov","middleInitial":"A.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":783551,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jackson, Pat J.","contributorId":206602,"corporation":false,"usgs":false,"family":"Jackson","given":"Pat","email":"","middleInitial":"J.","affiliations":[{"id":27489,"text":"Nevada Department of Wildlife","active":true,"usgs":false}],"preferred":false,"id":783552,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dinkins, Jonathan B.","contributorId":177565,"corporation":false,"usgs":false,"family":"Dinkins","given":"Jonathan","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":783553,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Howe, Kristy B.","contributorId":192078,"corporation":false,"usgs":false,"family":"Howe","given":"Kristy B.","affiliations":[],"preferred":false,"id":783554,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Moser, Ann M.","contributorId":206592,"corporation":false,"usgs":false,"family":"Moser","given":"Ann","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":783555,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Foster, Lee J.","contributorId":201654,"corporation":false,"usgs":false,"family":"Foster","given":"Lee","email":"","middleInitial":"J.","affiliations":[{"id":36223,"text":"Oregon Department of Fish and Wildlife","active":true,"usgs":false}],"preferred":false,"id":783556,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Delahunty, David J","contributorId":221820,"corporation":false,"usgs":false,"family":"Delahunty","given":"David","email":"","middleInitial":"J","affiliations":[{"id":38154,"text":"Idaho State University","active":true,"usgs":false}],"preferred":false,"id":783557,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70205932,"text":"ofr20191114 - 2020 - Multiple-well monitoring site adjacent to the Lost Hills oil field, Kern County, California","interactions":[],"lastModifiedDate":"2022-04-21T19:06:53.614311","indexId":"ofr20191114","displayToPublicDate":"2020-02-21T06:25:13","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2019-1114","displayTitle":"Multiple-Well Monitoring Site Adjacent to the Lost Hills Oil Field, Kern County, California","title":"Multiple-well monitoring site adjacent to the Lost Hills oil field, Kern County, California","docAbstract":"<p>The U.S. Geological Survey (USGS), in cooperation with the California State Water Resources Control Board, is evaluating several questions about oil and gas development and groundwater resources in California, including (1) the location of groundwater resources; (2) the proximity of oil and gas operations and groundwater and the geologic materials between them; (3) the location of evidence (or no evidence) of fluids from oil and gas sources in groundwater; and (4) the pathways or processes responsible when fluids from oil and gas sources are present in groundwater (U.S. Geological Survey, 2019). As part of this evaluation, the USGS installed a multiple-well monitoring site in the southern San Joaquin Valley near Lost Hills, California, adjacent to the Lost Hills oil field. Data collected at the Lost Hills multiple-well monitoring site (LHSP) provide information about the geology, hydrology, geophysics, and geochemistry of the aquifer system, thus enhancing understanding of relations between adjacent groundwater and the Lost Hills oil field in an area where there is little groundwater data. This report presents construction information for the LHSP and initial geohydrologic data collected from the site.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191114","collaboration":"Prepared in cooperation with California State Water Resources Control Board","usgsCitation":"Everett, R.R., Kjos, A., Brown, A.A., Gillespie, J.M., and McMahon, P.B., 2020, Multiple-well monitoring site adjacent to the Lost Hills oil field, Kern County, California: U.S. Geological Survey Open-File Report 2019–1114, 8 p., https://doi.org/10.3133/ofr20191114.","productDescription":"8 p.","numberOfPages":"8","onlineOnly":"Y","ipdsId":"IP-104714","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":437100,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9LGXIN8","text":"USGS data release","linkHelpText":"Aquifer test data for multiple-well monitoring site LHSP, Kern County, California"},{"id":399418,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109721.htm"},{"id":372427,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1114/coverthb.jpg"},{"id":372428,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1114/ofr20191114.pdf","text":"Report","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"California","county":"Kern County","otherGeospatial":"Lost Hills Oil Field","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -120.0167,\n              35.5294\n            ],\n            [\n              -119.4833,\n              35.5294\n            ],\n            [\n              -119.4833,\n              35.7667\n            ],\n            [\n              -120.0167,\n              35.7667\n            ],\n            [\n              -120.0167,\n              35.5294\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"mailto:dc_ca@usgs.gov\" data-mce-href=\"mailto:dc_ca@usgs.gov\">Director</a>,<br><a href=\"https://ca.water.usgs.gov/\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://ca.water.usgs.gov\">California Water Science Center</a><br><a href=\"https://usgs.gov/\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://usgs.gov\">U.S. Geological Survey</a><br>6000 J Street, Placer Hall<br>Sacramento, California 95819</p>","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"publishedDate":"2020-02-21","noUsgsAuthors":false,"publicationDate":"2020-02-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Everett, Rhett R. 0000-0001-7983-6270","orcid":"https://orcid.org/0000-0001-7983-6270","contributorId":208212,"corporation":false,"usgs":true,"family":"Everett","given":"Rhett","email":"","middleInitial":"R.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":772936,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kjos, Adam 0000-0002-2722-3306 adamkjos@usgs.gov","orcid":"https://orcid.org/0000-0002-2722-3306","contributorId":4130,"corporation":false,"usgs":true,"family":"Kjos","given":"Adam","email":"adamkjos@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":772937,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brown, Anthony A. 0000-0001-9925-0197","orcid":"https://orcid.org/0000-0001-9925-0197","contributorId":219711,"corporation":false,"usgs":true,"family":"Brown","given":"Anthony","email":"","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":772938,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gillespie, Janice M. 0000-0003-1667-3472","orcid":"https://orcid.org/0000-0003-1667-3472","contributorId":203915,"corporation":false,"usgs":true,"family":"Gillespie","given":"Janice M.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":false,"id":772939,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McMahon, Peter B. 0000-0001-7452-2379 pmcmahon@usgs.gov","orcid":"https://orcid.org/0000-0001-7452-2379","contributorId":724,"corporation":false,"usgs":true,"family":"McMahon","given":"Peter","email":"pmcmahon@usgs.gov","middleInitial":"B.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":772940,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70208018,"text":"sir20205004 - 2020 - Stormwater quality of infrastructure elements in Rapid City, South Dakota, 2016–18","interactions":[],"lastModifiedDate":"2022-04-25T20:51:46.467441","indexId":"sir20205004","displayToPublicDate":"2020-02-20T12:18:20","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2020-5004","displayTitle":"Stormwater Quality of Infrastructure Elements in Rapid City, South Dakota, 2016–18","title":"Stormwater quality of infrastructure elements in Rapid City, South Dakota, 2016–18","docAbstract":"<p>As runoff flows over the land or impervious surfaces (paved streets, parking lots, and building roofs), it accumulates debris, chemicals, sediment, and other contaminants that can adversely affect water quality if the runoff discharge remains untreated. Pathogens, commonly measured using fecal indicator bacteria such as <i>Escherichia coli</i>, enterococci, or fecal coliform, are the most-frequent cause of water-quality impairment in rivers and streams in the United States. Rapid Creek originates in the western Black Hills area and flows east through Rapid City, South Dakota, to its mouth at the Cheyenne River. The water quality of Rapid Creek is important because the reach that flows through Rapid City is a valuable spawning area for a self-sustaining trout fishery, is actively used for recreation, and is a seasonal municipal water supply for the City of Rapid City. These uses (fishery, recreation, and water supply) are considered beneficial uses by the South Dakota Department of Environment and Natural Resources. Numerical criteria have been established for total suspended solids and <i>Escherichia coli</i> concentrations, among other water-quality constituents, for these beneficial uses. The objectives of this study were to improve the method by which fecal indicator bacteria and total suspended solids are quantified in the urban drainages within Rapid City and to provide information that helps identify origins of fecal indicator bacteria and total suspended solids. This information can be used in hydrologic models to estimate fecal indicator bacteria and total suspended solid loading from certain infrastructure elements in urban environments.</p><p>Stormwater samples analyzed for <i>Escherichia coli</i>, total suspended solids, specific conductance, and pH were collected in three drainage basin flowpaths within Rapid City: Jackson, Wildwood, and the Eco Prayer Park. Data-collection activities for this study focused on upgradient urban flowpath elements during rainfall events. This approach builds upon previous stormwater assessments that characterized the water quality in urban basin outlets near the downstream end of the stormwater flowpaths. Within each flowpath group, 4–6 sites were selected to represent the various infrastructure elements of the runoff process. These elements included roof downspouts, parking lots, street curbs and gutters, open channels, underground storm sewers, and stormwater ponds or best-management practice facilities.</p><p>In general, the concentrations of <i>Escherichia coli</i> and total suspended solids increased in the downstream direction for all flowpath sites. The wash-off process after the first flush is evident for total suspended solids and specific conductance; however, <i>Escherichia coli</i> concentrations did not necessarily follow the same pattern. <i>Escherichia coli</i> concentrations in the latter part of the runoff period were similar to or greater than the initial concentrations of the first set of samples. Stormwater-quality data were summarized by infrastructure type (roof downspout, parking lot, street curb, and channel/storm sewer) to provide information about approximate water-quality concentrations originating at the upper end of urban flowpaths. <i>Escherichia coli</i> and total suspended solid concentrations were lowest in samples collected from locations most isolated from human influence (roof downspouts); the median concentrations at these sites were 4 most probable number per 100 milliliters and 15 milligrams per liter, respectively. The delivery potential of fecal indicator bacteria and sediment from parking lots and street curbs was similar; median concentrations of <i>Escherichia coli</i> and total suspended solids were around 150–220 most probable number per 100 milliliters and 56–86 milligrams per liter, respectively. The downstream receiving channels and storm sewers where stormwater was aggregated typically contained the highest <i>Escherichia coli</i> concentrations (median was 1,800 most probable number per 100 milliliters), but the total suspended solid concentrations were similar to upstream elements in the flowpath (median was 69 milligrams per liter). The data collected from this study demonstrate that stormwater is contaminated with fecal indicator bacteria upon initial contact with impervious surfaces and highlight the importance of controlling the volume of stormwater discharges into receiving waterbodies via storage structures and pervious elements. Diluting stormwater with high concentrations of <i>Escherichia coli</i> with the receiving water’s (Rapid Creek) lower concentration of <i>Escherichia coli</i> is likely the primary mechanism for meeting the beneficial-use criterion threshold of 235 most probable number per 100 milliliters. Although total suspended solid concentrations in the upper parts of the basin (parking lots and street curbs) also begin at concentrations (56 to 86 milligrams per liter) above the beneficial-use criterion for Rapid Creek (53 milligrams per liter), current stormwater-control practices (storage ponds, swales, and wetlands) may be able to reduce suspended-sediment concentrations to meet this threshold.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205004","collaboration":"Prepared in cooperation with the City of Rapid City","usgsCitation":"Hoogestraat, G.K., 2020, Stormwater quality of infrastructure elements in Rapid City, South Dakota, 2016–18: U.S. Geological Survey Scientific Investigations Report 2020–5004, 24 p., https://doi.org/10.3133/sir20205004.","productDescription":"Report: vii, 24 p.; Appendix; Dataset","numberOfPages":"36","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-108184","costCenters":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":399627,"rank":5,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109723.htm"},{"id":372437,"rank":4,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"National Water Information System database","linkHelpText":"– USGS water data for the Nation"},{"id":372436,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2020/5004/sir20205004_appendix1.csv","text":"Appendix 1","size":"12.8 kB","linkFileType":{"id":7,"text":"csv"},"description":"SIR 2020–5004 Appendix 1"},{"id":372434,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5004/coverthb.jpg"},{"id":372435,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5004/sir20205004.pdf","text":"Report","size":"3.50 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020–5004"}],"country":"United States","state":"South Dakota","city":"Rapid City","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -103.32,\n              44.0111\n            ],\n            [\n              -103.1364,\n              44.0111\n            ],\n            [\n              -103.1364,\n              44.125\n            ],\n            [\n              -103.32,\n              44.125\n            ],\n            [\n              -103.32,\n              44.0111\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p>Director, <a data-mce-href=\"https://www.usgs.gov/centers/dakota-water\" href=\"https://www.usgs.gov/centers/dakota-water\">Dakota Water Science Center</a> <br>U.S. Geological Survey<br>821 East Interstate Avenue<br>Bismarck, ND 58503 <br>1608 Mountain View Road<br>Rapid City, SD 57702</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Methods</li><li>Stormwater Quality of Infrastructure Elements</li><li>Summary</li><li>References Cited</li><li>Appendix 1 Stormwater-Quality Data</li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2020-02-20","noUsgsAuthors":false,"publicationDate":"2020-02-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Hoogestraat, Galen K. 0000-0001-5360-3903 ghoogest@usgs.gov","orcid":"https://orcid.org/0000-0001-5360-3903","contributorId":167614,"corporation":false,"usgs":true,"family":"Hoogestraat","given":"Galen","email":"ghoogest@usgs.gov","middleInitial":"K.","affiliations":[{"id":562,"text":"South Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":780163,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70208495,"text":"sir20195145 - 2020 - Hydrogeology and interactions of groundwater and surface water near Mill Creek and the Herring River, Wellfleet, Massachusetts, 2017–18","interactions":[],"lastModifiedDate":"2022-04-25T20:25:23.43755","indexId":"sir20195145","displayToPublicDate":"2020-02-20T12:00:00","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2019-5145","displayTitle":"Hydrogeology and Interactions of Groundwater and Surface Water Near Mill Creek and the Herring River, Wellfleet, Massachusetts, 2017–18","title":"Hydrogeology and interactions of groundwater and surface water near Mill Creek and the Herring River, Wellfleet, Massachusetts, 2017–18","docAbstract":"<p>Groundwater levels and stream stage were monitored by the U.S. Geological Survey, in cooperation with the Friends of Herring River, at 19 sites in the Mill Creek Basin, a tributary of the Herring River in Wellfleet, Massachusetts, on outer Cape Cod, to provide baseline data prior to a proposed restoration of tidal flow to the Herring River estuary at the Cape Cod National Seashore. Tidal flow in the Herring River has been restricted by a tide-control structure since 1909. Baseline data are necessary to understand current conditions and provide information on water levels for comparison to future water levels under the proposed Herring River restoration, which includes restoration of salt marshes by enhancing tidal flow to the Herring River and construction of a tide-control structure on Mill Creek to prevent the flooding of upstream private properties, including a golf course.</p><p>Analysis of data collected during monitoring-well installation at eight locations on or near the golf course and Mill Creek, along with analysis of existing information, determined that parts of the study area are underlain by salt marsh deposits up to 18 feet (ft) thick. These marsh deposits are directly underlain by estuarine sediments, and adjacent upland areas are underlain by medium to very coarse sand. The freshwater lens on the golf course is 70 ft thick or more.</p><p>Groundwater levels at individual wells in the study area fluctuated by 1.3 to 2.6 ft during the study period (June 1, 2017, to June 14, 2018). Total precipitation during this period was 60.8 inches, about 10 inches greater than the long-term (2000–17) annual average (50.3 inches). Groundwater levels on Cape Cod generally were normal to above normal during the study owing to the higher than normal precipitation. Tidal amplitudes of groundwater levels caused by daily fluctuations at nearby tidal waterbodies (M2 tidal harmonic) were as large as 0.12 ft at a well 105 ft from the tidally restricted Herring River and as large as 0.06 ft at a well 575 ft from Wellfleet Harbor. Tidal fluctuations in groundwater levels were generally limited to areas about 1,500 ft from the nearest tidal waterbody. Under the initial proposed restoration, where mean tides would be maintained similar to current conditions, tidal fluctuations would be restored to parts of Mill Creek, and subsequent tidal fluctuations in groundwater levels could increase at some of the areas closest to the proposed tide-control structure, but the fluctuations would be less than about 0.06 ft in magnitude.</p><p>Regression models were used to describe the variability of daily mean tidally filtered groundwater levels and daily maximum stream stage in Mill Creek. Significant independent variables for the groundwater-level model included daily tidally filtered Wellfleet Harbor stage with a lag time of zero to 2 days, 7-day precipitation, the growing degree days (50 degrees Fahrenheit), and the quartile of groundwater levels relative to a long period of record at a nearby observation well.</p><p>Significant independent variables to predict the Mill Creek stage included daily mean groundwater levels in nearby wells, 7-day precipitation, growing degree days (50 degrees Fahrenheit), and a binary indicator of either a flooded or nonflooded condition on the golf course near Mill Creek. Flooding in Mill Creek occurred primarily when groundwater levels at nearby wells reached certain thresholds, when the precipitation in the preceding 7 days was at least 0.92–1.04 inches, and during the nongrowing season.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195145","collaboration":"Prepared in cooperation with the Friends of Herring River","usgsCitation":"Mullaney, J.R., Barclay, J.R., Laabs, K.L., and Lavallee, K.D., 2020, Hydrogeology and interactions of groundwater and surface water near Mill Creek and the Herring River, Wellfleet, Massachusetts, 2017–18: U.S. Geological Survey Scientific Investigations Report 2019–5145, 60 p., https://doi.org/10.3133/sir20195145.","productDescription":"Report: viii, 60 p.; Data Release; Project Site","numberOfPages":"72","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-103306","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":437103,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P903HI9K","text":"USGS data release","linkHelpText":"Data on Models to Describe Groundwater Levels and Stream Stage near the Herring River, Wellfleet, Cape Cod, Massachusetts, 2017-2022"},{"id":399619,"rank":5,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109683.htm"},{"id":372270,"rank":4,"type":{"id":18,"text":"Project Site"},"url":"https://www.usgs.gov/centers/new-england-water/science/groundwater-and-surface-water-monitoring-mill-creek-watershed","text":"Project site","linkHelpText":"- Groundwater and Surface-Water Monitoring in the Mill Creek Watershed, Wellfleet and Truro, Massachusetts"},{"id":372269,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9T167II","text":"USGS data release","linkHelpText":"Data on Tidally Filtered Groundwater and Estuary Water Levels, and Climatological Data Near Mill Creek and the Herring River, Cape Cod, Wellfleet, Massachusetts, 2017–2018"},{"id":372451,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5145/sir20195145.pdf","text":"Report","size":"6.14 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019-5145"},{"id":372267,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5145/coverthb2.jpg"}],"country":"United States","state":"Massachusetts","county":"Barnstable County","city":"Wellfleet","otherGeospatial":"Mill Creek, Herring River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -70.06719589233398,\n              41.92412111618309\n            ],\n            [\n              -70.04968643188475,\n              41.92412111618309\n            ],\n            [\n              -70.04968643188475,\n              41.9377858285046\n            ],\n            [\n              -70.06719589233398,\n              41.9377858285046\n            ],\n            [\n              -70.06719589233398,\n              41.92412111618309\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"mailto:dc_nweng@usgs.gov\" data-mce-href=\"mailto:dc_nweng@usgs.gov\">Director</a>, <a href=\"http://www.usgs.gov/centers/new-england-water\" data-mce-href=\"http://www.usgs.gov/centers/new-england-water\">New England Water Science Center</a><br>U.S. Geological Survey<br>331 Commerce Way, Suite 2<br>Pembroke, New Hampshire 03275</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Methods of Data Collection and Analysis</li><li>Lithologic and Water-Level Data at the Mill Creek Study Area</li><li>Summary and Conclusions</li><li>References Cited</li><li>Appendix 1. Graphs of Water Levels in Wells Monitored for the Study of the Mill Creek Study Area, June 2017–June 2018</li><li>Appendix 2. Regression Coefficients and Metrics for Linear Regression Models Describing the Variability in Groundwater Levels and Surface-Water Levels Near the Herring River, Wellfleet, Massachusetts, From June 2017 To June 2018</li></ul>","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"publishedDate":"2020-02-12","noUsgsAuthors":false,"publicationDate":"2020-02-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Mullaney, John R. 0000-0003-4936-5046 jmullane@usgs.gov","orcid":"https://orcid.org/0000-0003-4936-5046","contributorId":1957,"corporation":false,"usgs":true,"family":"Mullaney","given":"John","email":"jmullane@usgs.gov","middleInitial":"R.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":196,"text":"Connecticut Water Science Center","active":true,"usgs":true}],"preferred":true,"id":782150,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barclay, Janet R. 0000-0003-1643-6901 jbarclay@usgs.gov","orcid":"https://orcid.org/0000-0003-1643-6901","contributorId":222437,"corporation":false,"usgs":true,"family":"Barclay","given":"Janet","email":"jbarclay@usgs.gov","middleInitial":"R.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":782151,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Laabs, Kaitlin L. 0000-0002-7798-3485 klaabs@usgs.gov","orcid":"https://orcid.org/0000-0002-7798-3485","contributorId":222438,"corporation":false,"usgs":true,"family":"Laabs","given":"Kaitlin","email":"klaabs@usgs.gov","middleInitial":"L.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":782152,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lavallee, Katherine D. 0000-0003-0747-9344","orcid":"https://orcid.org/0000-0003-0747-9344","contributorId":222439,"corporation":false,"usgs":false,"family":"Lavallee","given":"Katherine","email":"","middleInitial":"D.","affiliations":[],"preferred":true,"id":782153,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
]}