{"pageNumber":"635","pageRowStart":"15850","pageSize":"25","recordCount":184883,"records":[{"id":70209726,"text":"fs20203025 - 2020 - Groundwater quality in the Redding–Red Bluff shallow aquifer study unit of the northern Sacramento Valley, California","interactions":[],"lastModifiedDate":"2020-10-16T16:35:55.018658","indexId":"fs20203025","displayToPublicDate":"2020-04-23T07:35:40","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":"2020-3025","displayTitle":"Groundwater Quality in the Redding–Red Bluff Shallow Aquifer Study Unit of the Northern Sacramento Valley, California","title":"Groundwater quality in the Redding–Red Bluff shallow aquifer study unit of the northern Sacramento Valley, California","docAbstract":"<p><span>Groundwater provides more than 40 percent of California’s drinking water. To protect this vital resource, the State of California created the Groundwater Ambient Monitoring and Assessment (GAMA) Program. The Priority Basin Project of the GAMA Program provides a comprehensive assessment of the State’s groundwater quality and increases public access to groundwater-quality information. Private domestic and small system drinking water wells in the Redding–Red Bluff study unit primarily draw from shallow aquifers which are the target for this assessment.</span></p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20203025","collaboration":"Prepared in cooperation with the California State Water Resources Control Board","usgsCitation":"Harkness, J.S., and Shelton, J.L., 2020, Groundwater quality in the Redding–Red Bluff shallow aquifer study unit of the northern Sacramento Valley, California: U.S. Geological Survey Fact Sheet 2020–3025, 4 p., https://doi.org/10.3133/fs20203025.","productDescription":"4 p.","numberOfPages":"4","ipdsId":"IP-114766","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":437016,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9ZKAH3O","text":"USGS data release","linkHelpText":"Groundwater-quality Data in the Redding-Red Bluff Shallow Aquifer Study Unit, 2018-2019: Results from the California GAMA Priority Basin Project"},{"id":374207,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2020/3025/fs20203025.pdf","text":"Report","size":"4 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":374206,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2020/3025/coverthb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Northern Sacramento Valley","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -122.882080078125,\n              39.70296052957233\n            ],\n            [\n              -121.58569335937501,\n              39.70296052957233\n            ],\n            [\n              -121.58569335937501,\n              40.97575093157534\n            ],\n            [\n              -122.882080078125,\n              40.97575093157534\n            ],\n            [\n              -122.882080078125,\n              39.70296052957233\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"https://ca.water.usgs.gov/gama\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://ca.water.usgs.gov/gama\">GAMA Project Chief</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 data-mce-href=\"https://usgs.gov\" href=\"https://usgs.gov\" target=\"_blank\" rel=\"noopener\">U.S. Geological Survey</a><br>6000 J Street, Placer Hall<br>Sacramento, CA 95819<br>Telephone number: (916) 278-3000</p><p><a href=\"https://www.waterboards.ca.gov/gama\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.waterboards.ca.gov/gama\">GAMA Program Unit Chief</a><br>State Water Resources Control Board<br>Division of Water Quality<br>PO Box 2231, Sacramento, CA 95812<br>Telephone number: (916) 341-5855</p>","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"publishedDate":"2020-04-23","noUsgsAuthors":false,"publicationDate":"2020-04-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Harkness, Jennifer S. 0000-0001-9050-2570 jharkness@usgs.gov","orcid":"https://orcid.org/0000-0001-9050-2570","contributorId":224299,"corporation":false,"usgs":true,"family":"Harkness","given":"Jennifer","email":"jharkness@usgs.gov","middleInitial":"S.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":787688,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shelton, Jennifer L. 0000-0001-8508-0270 jshelton@usgs.gov","orcid":"https://orcid.org/0000-0001-8508-0270","contributorId":1155,"corporation":false,"usgs":true,"family":"Shelton","given":"Jennifer","email":"jshelton@usgs.gov","middleInitial":"L.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":787687,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70228656,"text":"70228656 - 2020 - Assessment of spatial genetic structure to identify populations at risk for infection of an emerging epizootic disease","interactions":[],"lastModifiedDate":"2022-02-16T17:55:01.617963","indexId":"70228656","displayToPublicDate":"2020-04-22T11:48:13","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Assessment of spatial genetic structure to identify populations at risk for infection of an emerging epizootic disease","docAbstract":"<ol class=\"\"><li>Understanding the geographic extent and connectivity of wildlife populations can provide important insights into the management of disease outbreaks but defining patterns of population structure is difficult for widely distributed species. Landscape genetic analyses are powerful methods for identifying cryptic structure and movement patterns that may be associated with spatial epizootic patterns in such cases.</li><li>We characterized patterns of population substructure and connectivity using microsatellite genotypes from 2,222 white-tailed deer (<i>Odocoileus virginianus</i>) in the Mid-Atlantic region of the United States, a region where chronic wasting disease was first detected in 2009. The goal of this study was to evaluate the juxtaposition between population structure, landscape features that influence gene flow, and current disease management units.</li><li>Clustering analyses identified four to five subpopulations in this region, the edges of which corresponded to ecophysiographic provinces. Subpopulations were further partitioned into 11 clusters with subtle (<i>F</i><sub>ST</sub>&nbsp;≤&nbsp;0.041), but significant genetic differentiation. Genetic differentiation was lower and migration rates were higher among neighboring genetic clusters, indicating an underlying genetic cline. Genetic discontinuities were associated with topographic barriers, however.</li><li>Resistance surface modeling indicated that gene flow was diffuse in homogenous landscapes, but the direction and extent of gene flow were influenced by forest cover, traffic volume, and elevational relief in subregions heterogeneous for these landscape features. Chronic wasting disease primarily occurred among genetic clusters within a single subpopulation and along corridors of high landscape connectivity.</li><li>These results may suggest a possible correlation between population substructure, landscape connectivity, and the occurrence of diseases for widespread species. Considering these factors may be useful in delineating effective management units, although only the largest features produced appreciable differences in subpopulation structure. Disease mitigation strategies implemented at the scale of ecophysiographic provinces are likely to be more effective than those implemented at finer scales.</li></ol>","language":"English","publisher":"Wiley","doi":"10.1002/ece3.6161","usgsCitation":"Miller, W., Miller-Butterworth, C.M., Diefenbach, D.R., and Walter, W., 2020, Assessment of spatial genetic structure to identify populations at risk for infection of an emerging epizootic disease: Ecology and Evolution, v. 10, no. 9, p. 3977-3990, https://doi.org/10.1002/ece3.6161.","productDescription":"14 p.","startPage":"3977","endPage":"3990","ipdsId":"IP-113463","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":456977,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.6161","text":"Publisher Index Page"},{"id":396024,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maryland, Pennsylvania, Virginia","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -80.44189453125,\n              38.95940879245423\n            ],\n            [\n              -77.14599609375,\n              38.95940879245423\n            ],\n            [\n              -77.14599609375,\n              41.86956082699455\n            ],\n            [\n              -80.44189453125,\n              41.86956082699455\n            ],\n            [\n              -80.44189453125,\n              38.95940879245423\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"10","issue":"9","noUsgsAuthors":false,"publicationDate":"2020-04-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Miller, William L.","contributorId":279431,"corporation":false,"usgs":false,"family":"Miller","given":"William L.","affiliations":[{"id":36985,"text":"Penn State University","active":true,"usgs":false}],"preferred":false,"id":834945,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Miller-Butterworth, Cassandra M.","contributorId":279432,"corporation":false,"usgs":false,"family":"Miller-Butterworth","given":"Cassandra","email":"","middleInitial":"M.","affiliations":[{"id":36985,"text":"Penn State University","active":true,"usgs":false}],"preferred":false,"id":834946,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Diefenbach, Duane R. 0000-0001-5111-1147 drd11@usgs.gov","orcid":"https://orcid.org/0000-0001-5111-1147","contributorId":5235,"corporation":false,"usgs":true,"family":"Diefenbach","given":"Duane","email":"drd11@usgs.gov","middleInitial":"R.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":834944,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Walter, W. David 0000-0003-3068-1073","orcid":"https://orcid.org/0000-0003-3068-1073","contributorId":219540,"corporation":false,"usgs":true,"family":"Walter","given":"W. David","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":834943,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70209731,"text":"70209731 - 2020 - Mitigating land subsidence in the Coachella Valley, California, USA: An emerging success story","interactions":[],"lastModifiedDate":"2020-04-23T15:30:09.031759","indexId":"70209731","displayToPublicDate":"2020-04-22T10:23:24","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5272,"text":"Proceedings of the International Association of Hydrological Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Mitigating land subsidence in the Coachella Valley, California, USA: An emerging success story","docAbstract":"<p><span>Groundwater has been a major source of agricultural, municipal, and domestic water supply since the early 1920s in the Coachella Valley, California, USA. Land subsidence, resulting from aquifer-system compaction and groundwater-level declines, has been a concern of the Coachella Valley Water District (CVWD) since the mid-1990s. As a result, the CVWD has implemented several projects to address groundwater overdraft that fall under three categories – groundwater substitution, conservation, and managed aquifer-recharge (MAR). The implementation of three projects in particular – replacing groundwater extraction with surface water from the Colorado River and recycled water (Mid-Valley Pipeline project), reducing water usage by tiered-rate costs, and increasing groundwater recharge at the Thomas E. Levy Groundwater Replenishment Facility – are potentially linked to markedly improved groundwater levels and subsidence conditions, including in some of the historically most overdrafted areas in the southern Coachella Valley. Groundwater-level and subsidence monitoring have tracked the effect these projects have had on the aquifer system. Prior to about 2010, water levels persistently declined, and some had reached historically low levels by 2010. Since about 2010, however, groundwater levels have stabilized or partially recovered, and subsidence has stopped or slowed substantially almost everywhere it previously had been observed; uplift was observed in some areas. Furthermore, results of Interferometric Synthetic Aperture Radar analyses for 1995–2017 indicate that as much as about 0.6 m of subsidence occurred; nearly all of which occurred prior to 2010. Continued monitoring of water levels and subsidence is necessary to inform the CVWD about future mitigation measures. The water management strategies implemented by the CVWD can inform managers of other overdrafted and subsidence-prone basins as they seek solutions to reduce overdraft and subsidence.</span></p>","language":"English","publisher":"Copernicus Publications","doi":"10.5194/piahs-382-809-2020","collaboration":"","usgsCitation":"Sneed, M., and Brandt, J.T., 2020, Mitigating land subsidence in the Coachella Valley, California, USA: An emerging success story: Proceedings of the International Association of Hydrological Sciences, v. 382, p. 809-813, https://doi.org/10.5194/piahs-382-809-2020.","productDescription":"5 p.","startPage":"809","endPage":"813","ipdsId":"IP-111082","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":456979,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/piahs-382-809-2020","text":"Publisher Index Page"},{"id":374224,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Coachella Valley","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -116.37954711914062,\n              33.53223722395908\n            ],\n            [\n              -116.02523803710938,\n              33.53223722395908\n            ],\n            [\n              -116.02523803710938,\n              33.82023008524739\n            ],\n            [\n              -116.37954711914062,\n              33.82023008524739\n            ],\n            [\n              -116.37954711914062,\n              33.53223722395908\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"382","noUsgsAuthors":false,"publicationDate":"2020-04-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Sneed, Michelle 0000-0002-8180-382X micsneed@usgs.gov","orcid":"https://orcid.org/0000-0002-8180-382X","contributorId":155,"corporation":false,"usgs":true,"family":"Sneed","given":"Michelle","email":"micsneed@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":787696,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brandt, Justin T. 0000-0002-9397-6824 jbrandt@usgs.gov","orcid":"https://orcid.org/0000-0002-9397-6824","contributorId":157,"corporation":false,"usgs":true,"family":"Brandt","given":"Justin","email":"jbrandt@usgs.gov","middleInitial":"T.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":787697,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70209736,"text":"70209736 - 2020 - Airborne lidar and electro-optical imagery along surface ruptures of the 2019 Ridgecrest earthquake sequence, Southern California","interactions":[],"lastModifiedDate":"2020-07-09T14:51:19.4533","indexId":"70209736","displayToPublicDate":"2020-04-22T09:55:23","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"Airborne lidar and electro-optical imagery along surface ruptures of the 2019 Ridgecrest earthquake sequence, Southern California","docAbstract":"Surface rupture from the 2019 Ridgecrest earthquake sequence, initially associated with the M 6.4 foreshock, occurred on July 4 on a ~17 km long, northeast-southwest oriented, left-lateral zone of faulting. Following the M 7.1 mainshock on July 5 (local time), extensive northwest-southeast-oriented, right-lateral faulting was then also mapped along a ~50 km long zone of faults, including sub-parallel splays in several areas. The largest slip was observed in the epicentral area, and crossing the dry lakebed of China Lake to the southeast. Surface fault rupture mapping by a large team, reported elsewhere, was used to guide the airborne data acquisition reported here. Rapid rupture mapping allowed for accurate and efficient flight line planning for the high-resolution lidar and aerial photography. Flight line planning trade-offs were considered to allocate the medium (25 pulses per square meter, or ppsm) and high resolution (80 ppsm) lidar data collection polygons. The National Center for Airborne Laser Mapping (NCALM) acquired the airborne imagery with a Titan multispectral lidar system and DiMAC aerial digital camera, and USGS acquired GPS ground control data. This effort required extensive coordination with the Navy as much of the airborne data acquisition occurred within their restricted airspace at the China Lake Ranges.","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220190338","usgsCitation":"Hudnut, K.W., Brooks, B.A., Scharer, K.M., Hernandez, J.L., Dawson, T.E., Oskin, M.E., Arrowsmith, J.R., Goulet, C.A., Blake, K., Boggie, M.A., Bork, S., Craig L. Glennie, Fernandez-Diaz, J., Singhania, A., Hauser, D., and Sorhus, S., 2020, Airborne lidar and electro-optical imagery along surface ruptures of the 2019 Ridgecrest earthquake sequence, Southern California: Seismological Research Letters, v. 91, no. 4, p. 2096-2107, https://doi.org/10.1785/0220190338.","productDescription":"11 p.","startPage":"2096","endPage":"2107","ipdsId":"IP-114239","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":374220,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Calilfornia","otherGeospatial":"Ridgecrest Earthquake Sequence","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -118.125,\n              35.1154153142536\n            ],\n            [\n              -117.2076416015625,\n              35.1154153142536\n            ],\n            [\n              -117.2076416015625,\n              36.27085020723902\n            ],\n            [\n              -118.125,\n              36.27085020723902\n            ],\n            [\n              -118.125,\n              35.1154153142536\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"91","issue":"4","noUsgsAuthors":false,"publicationDate":"2020-04-22","publicationStatus":"PW","contributors":{"editors":[{"text":"Brooks, Benjamin A. 0000-0001-7954-6281 bbrooks@usgs.gov","orcid":"https://orcid.org/0000-0001-7954-6281","contributorId":5237,"corporation":false,"usgs":true,"family":"Brooks","given":"Benjamin","email":"bbrooks@usgs.gov","middleInitial":"A.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":787726,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Scharer, Katherine M. 0000-0003-2811-2496","orcid":"https://orcid.org/0000-0003-2811-2496","contributorId":217361,"corporation":false,"usgs":true,"family":"Scharer","given":"Katherine M.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":787727,"contributorType":{"id":2,"text":"Editors"},"rank":3},{"text":"Hernandez, Janis","contributorId":216335,"corporation":false,"usgs":false,"family":"Hernandez","given":"Janis","affiliations":[{"id":12640,"text":"California Geological Survey","active":true,"usgs":false}],"preferred":false,"id":787728,"contributorType":{"id":2,"text":"Editors"},"rank":4},{"text":"Dawson, Timothy E.","contributorId":24429,"corporation":false,"usgs":false,"family":"Dawson","given":"Timothy","email":"","middleInitial":"E.","affiliations":[{"id":7099,"text":"Calif. 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National Center for Airborne Laser Mapping","active":true,"usgs":false}],"preferred":false,"id":787737,"contributorType":{"id":2,"text":"Editors"},"rank":13},{"text":"Singhania, Abhinav","contributorId":224313,"corporation":false,"usgs":false,"family":"Singhania","given":"Abhinav","email":"","affiliations":[{"id":40857,"text":"Univ. of Houston - National Center for Airborne Laser Mapping","active":true,"usgs":false}],"preferred":false,"id":787738,"contributorType":{"id":2,"text":"Editors"},"rank":14},{"text":"Hauser, Darren L.","contributorId":202340,"corporation":false,"usgs":false,"family":"Hauser","given":"Darren","email":"","middleInitial":"L.","affiliations":[{"id":36391,"text":"University of Houston","active":true,"usgs":false}],"preferred":false,"id":787739,"contributorType":{"id":2,"text":"Editors"},"rank":15},{"text":"Sorhus, Sven","contributorId":224314,"corporation":false,"usgs":false,"family":"Sorhus","given":"Sven","email":"","affiliations":[{"id":40857,"text":"Univ. of Houston - National Center for Airborne Laser Mapping","active":true,"usgs":false}],"preferred":false,"id":787740,"contributorType":{"id":2,"text":"Editors"},"rank":16}],"authors":[{"text":"Hudnut, Kenneth W. 0000-0002-3168-4797 hudnut@usgs.gov","orcid":"https://orcid.org/0000-0002-3168-4797","contributorId":2550,"corporation":false,"usgs":true,"family":"Hudnut","given":"Kenneth","email":"hudnut@usgs.gov","middleInitial":"W.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":508,"text":"Office of the AD Hazards","active":true,"usgs":true}],"preferred":true,"id":787725,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brooks, Benjamin A. 0000-0001-7954-6281 bbrooks@usgs.gov","orcid":"https://orcid.org/0000-0001-7954-6281","contributorId":5237,"corporation":false,"usgs":true,"family":"Brooks","given":"Benjamin","email":"bbrooks@usgs.gov","middleInitial":"A.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":787759,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Scharer, Katherine M. 0000-0003-2811-2496 kscharer@usgs.gov","orcid":"https://orcid.org/0000-0003-2811-2496","contributorId":3385,"corporation":false,"usgs":true,"family":"Scharer","given":"Katherine","email":"kscharer@usgs.gov","middleInitial":"M.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":787760,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hernandez, Janis L.","contributorId":90603,"corporation":false,"usgs":true,"family":"Hernandez","given":"Janis","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":787761,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dawson, Timothy E.","contributorId":24429,"corporation":false,"usgs":false,"family":"Dawson","given":"Timothy","email":"","middleInitial":"E.","affiliations":[{"id":7099,"text":"Calif. Geol. Survey","active":true,"usgs":false}],"preferred":false,"id":787762,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Oskin, Michael E.","contributorId":191806,"corporation":false,"usgs":false,"family":"Oskin","given":"Michael","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":787763,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Arrowsmith, J. Ramon","contributorId":101185,"corporation":false,"usgs":true,"family":"Arrowsmith","given":"J.","email":"","middleInitial":"Ramon","affiliations":[],"preferred":false,"id":787764,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Goulet, Christine A. 0000-0002-7643-357X","orcid":"https://orcid.org/0000-0002-7643-357X","contributorId":194805,"corporation":false,"usgs":false,"family":"Goulet","given":"Christine","email":"","middleInitial":"A.","affiliations":[{"id":13249,"text":"University of Southern California","active":true,"usgs":false}],"preferred":false,"id":787765,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Blake, Kelly","contributorId":197142,"corporation":false,"usgs":false,"family":"Blake","given":"Kelly","affiliations":[],"preferred":false,"id":787766,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Boggie, Matthew A.","contributorId":198068,"corporation":false,"usgs":false,"family":"Boggie","given":"Matthew","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":787767,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Bork, Stephan","contributorId":224311,"corporation":false,"usgs":false,"family":"Bork","given":"Stephan","email":"","affiliations":[{"id":13444,"text":"US Navy","active":true,"usgs":false}],"preferred":false,"id":787768,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Craig L. Glennie","contributorId":202334,"corporation":false,"usgs":false,"family":"Craig L. Glennie","affiliations":[{"id":36391,"text":"University of Houston","active":true,"usgs":false}],"preferred":false,"id":787769,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Fernandez-Diaz, J.C.","contributorId":224312,"corporation":false,"usgs":false,"family":"Fernandez-Diaz","given":"J.C.","email":"","affiliations":[{"id":40857,"text":"Univ. of Houston - National Center for Airborne Laser Mapping","active":true,"usgs":false}],"preferred":false,"id":787770,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Singhania, Abhinav","contributorId":224313,"corporation":false,"usgs":false,"family":"Singhania","given":"Abhinav","email":"","affiliations":[{"id":40857,"text":"Univ. of Houston - National Center for Airborne Laser Mapping","active":true,"usgs":false}],"preferred":false,"id":787771,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Hauser, Darren","contributorId":34061,"corporation":false,"usgs":true,"family":"Hauser","given":"Darren","affiliations":[],"preferred":false,"id":787772,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Sorhus, Sven","contributorId":224314,"corporation":false,"usgs":false,"family":"Sorhus","given":"Sven","email":"","affiliations":[{"id":40857,"text":"Univ. of Houston - National Center for Airborne Laser Mapping","active":true,"usgs":false}],"preferred":false,"id":787773,"contributorType":{"id":1,"text":"Authors"},"rank":16}]}}
,{"id":70211500,"text":"70211500 - 2020 - Carbon sources in the sediments of a restoring vs. historically unaltered salt marsh","interactions":[],"lastModifiedDate":"2020-07-29T14:54:52.589832","indexId":"70211500","displayToPublicDate":"2020-04-22T09:48:57","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1584,"text":"Estuaries and Coasts","active":true,"publicationSubtype":{"id":10}},"title":"Carbon sources in the sediments of a restoring vs. historically unaltered salt marsh","docAbstract":"<div id=\"Abs1-section\" class=\"c-article-section\"><div id=\"Abs1-content\" class=\"c-article-section__content\"><p>Salt marshes provide the important ecosystem service of carbon storage in their sediments; however, little is known about the sources of such carbon and whether they differ between historically unaltered and restoring systems. In this study, stable isotope analysis was used to quantify carbon sources in a restoring, sparsely vegetated marsh (Restoring) and an adjacent, historically unaltered marsh (Reference) in the Nisqually River Delta (NRD) of Washington, USA. Three sediment cores were collected at “Inland” and “Seaward” locations at both marshes ~ 6&nbsp;years after restoration. Benthic diatoms, C3 plants, C4 plants, and particulate organic matter (POM) were collected throughout the NRD. δ<sup>13</sup>C and δ<sup>15</sup>N values of sources and sediments were used in a Bayesian stable isotope mixing model to determine the contribution of each carbon source to the sediments of both marshes. Autochthonous marsh C3 plants contributed 73 ± 10% (98&nbsp;g C m<sup>−2</sup>&nbsp;year<sup>−1</sup>) and 89 ± 11% (119&nbsp;g C m<sup>−2</sup>&nbsp;year<sup>−1</sup>) to Reference-Inland and Reference-Seaward sediment carbon sinks, respectively. In contrast, the sediment carbon sink at the Restoring Marsh received a broad assortment of predominantly allochthonous materials, which varied in relative contribution based on source distance and abundance. Marsh POM contributed the most to Restoring-Seaward (42 ± 34%) (69&nbsp;g C m<sup>−2</sup>&nbsp;year<sup>−1</sup>) followed by Riverine POM at Restoring-Inland (32 ± 41%) (52&nbsp;g C m<sup>−2</sup>&nbsp;year<sup>−1</sup>). Overall, this study demonstrates that largely unvegetated, restoring marshes can accumulate carbon by relying predominantly on allochthonous material, which comes mainly from the most abundant and closest estuarine sources.</p></div></div><div id=\"Sec1-section\" class=\"c-article-section\"><br></div><p>ces.</p>","language":"English","publisher":"Springer","doi":"10.1007/s12237-020-00748-7","usgsCitation":"Drexler, J.Z., Davis, M.J., Woo, I., and De La Cruz, S.E., 2020, Carbon sources in the sediments of a restoring vs. historically unaltered salt marsh: Estuaries and Coasts, v. 43, p. 1345-1360, https://doi.org/10.1007/s12237-020-00748-7.","productDescription":"16 p.","startPage":"1345","endPage":"1360","ipdsId":"IP-109595","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":456984,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s12237-020-00748-7","text":"Publisher Index Page"},{"id":376842,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Nisqually River Delta","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -123.3819580078125,\n              46.68713141244413\n            ],\n            [\n              -122.0855712890625,\n              46.68713141244413\n            ],\n            [\n              -122.0855712890625,\n              47.51349065484327\n            ],\n            [\n              -123.3819580078125,\n              47.51349065484327\n            ],\n            [\n              -123.3819580078125,\n              46.68713141244413\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"43","noUsgsAuthors":false,"publicationDate":"2020-04-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Drexler, Judith Z. 0000-0002-0127-3866 jdrexler@usgs.gov","orcid":"https://orcid.org/0000-0002-0127-3866","contributorId":167492,"corporation":false,"usgs":true,"family":"Drexler","given":"Judith","email":"jdrexler@usgs.gov","middleInitial":"Z.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":794369,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Davis, Melanie J. 0000-0003-1734-7177","orcid":"https://orcid.org/0000-0003-1734-7177","contributorId":202773,"corporation":false,"usgs":true,"family":"Davis","given":"Melanie","email":"","middleInitial":"J.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":794370,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Woo, Isa 0000-0002-8447-9236 iwoo@usgs.gov","orcid":"https://orcid.org/0000-0002-8447-9236","contributorId":2524,"corporation":false,"usgs":true,"family":"Woo","given":"Isa","email":"iwoo@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":794371,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"De La Cruz, Susan E.W. 0000-0001-6315-0864 sdelacruz@usgs.gov","orcid":"https://orcid.org/0000-0001-6315-0864","contributorId":3248,"corporation":false,"usgs":true,"family":"De La Cruz","given":"Susan","email":"sdelacruz@usgs.gov","middleInitial":"E.W.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":794372,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70217612,"text":"70217612 - 2020 - Simulated increases in fire activity reinforce shrub conversion in a southwestern US forest","interactions":[],"lastModifiedDate":"2021-01-25T15:03:59.909005","indexId":"70217612","displayToPublicDate":"2020-04-22T08:57:23","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1478,"text":"Ecosystems","active":true,"publicationSubtype":{"id":10}},"title":"Simulated increases in fire activity reinforce shrub conversion in a southwestern US forest","docAbstract":"<p><span>Fire exclusion in historically frequent-fire forests of the southwestern United States has altered forest structure and increased the probability of high-severity fire. Warmer and drier conditions, coupled with dispersal distance limitations, are impeding tree seedling establishment and survival following high-severity fire. High-severity patches are commonly dominated by non-forest vegetation, a state that can be reinforced by subsequent fire events. We sought to determine the influence of fire probability on post-fire vegetation development in a severely burned landscape in New Mexico, USA. We used LANDIS-II to simulate three fire probability scenarios—historical fire probability, contemporary fire probability, and the mean of the two—with contemporary climate. As fire probability increased, the mean size of the largest fires and the mean landscape fire severity increased. These changes in fire characteristics resulted in decreased total aboveground biomass and photosynthetic capacity on the landscape after 50&nbsp;years. Additionally, the distribution of individual species biomass shifted, with early successional species, especially those that resprout after fire, increasing as a fraction of total biomass with increasing fire occurrence. Counter to empirical data, our simulations did not show a conifer establishment limitation, suggesting a source of uncertainty that will need to be addressed to improve projections of forest dynamics under future climate. Even without limited conifer regeneration, continued increases in fire frequency are likely to favor resprouting species and result in a loss of forest biomass and ecosystem productivity in this southwestern forest landscape.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s10021-020-00498-4","usgsCitation":"Keyser, A.R., Krofchek, D.J., Remy, C.C., Allen, C.D., and Hurteau, M.D., 2020, Simulated increases in fire activity reinforce shrub conversion in a southwestern US forest: Ecosystems, v. 23, p. 1702-1713, https://doi.org/10.1007/s10021-020-00498-4.","productDescription":"12 p.","startPage":"1702","endPage":"1713","ipdsId":"IP-117785","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":488249,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://hal.science/hal-05042363","text":"External Repository"},{"id":382542,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Mexico","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -106.8695068359375,\n              35.706377408871774\n            ],\n            [\n              -106.3970947265625,\n              35.706377408871774\n            ],\n            [\n              -106.3970947265625,\n              36.10681461011844\n            ],\n            [\n              -106.8695068359375,\n              36.10681461011844\n            ],\n            [\n              -106.8695068359375,\n              35.706377408871774\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"23","noUsgsAuthors":false,"publicationDate":"2020-04-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Keyser, Alisa R.","contributorId":248331,"corporation":false,"usgs":false,"family":"Keyser","given":"Alisa","email":"","middleInitial":"R.","affiliations":[{"id":49860,"text":"Univ. of New Mexico","active":true,"usgs":false}],"preferred":false,"id":808892,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Krofchek, Dan J.","contributorId":248332,"corporation":false,"usgs":false,"family":"Krofchek","given":"Dan","email":"","middleInitial":"J.","affiliations":[{"id":35754,"text":"Univ of New Mexico","active":true,"usgs":false}],"preferred":false,"id":808893,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Remy, Cecile C.","contributorId":248333,"corporation":false,"usgs":false,"family":"Remy","given":"Cecile","email":"","middleInitial":"C.","affiliations":[{"id":35754,"text":"Univ of New Mexico","active":true,"usgs":false}],"preferred":false,"id":808894,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Allen, Craig D. 0000-0002-8777-5989 craig_allen@usgs.gov","orcid":"https://orcid.org/0000-0002-8777-5989","contributorId":2597,"corporation":false,"usgs":true,"family":"Allen","given":"Craig","email":"craig_allen@usgs.gov","middleInitial":"D.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":808895,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hurteau, Matthew D.","contributorId":211635,"corporation":false,"usgs":false,"family":"Hurteau","given":"Matthew","email":"","middleInitial":"D.","affiliations":[{"id":38287,"text":"Department of Biology, University of New Mexico, Albuquerque, NM 87131, USA","active":true,"usgs":false}],"preferred":false,"id":808896,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70209787,"text":"70209787 - 2020 - Detection and measurement of land subsidence and uplift using interferometric synthetic aperture radar, San Diego, California, USA, 2016–2018","interactions":[],"lastModifiedDate":"2020-04-29T13:17:26.480601","indexId":"70209787","displayToPublicDate":"2020-04-22T08:16:45","publicationYear":"2020","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Detection and measurement of land subsidence and uplift using interferometric synthetic aperture radar, San Diego, California, USA, 2016–2018","docAbstract":"Land subsidence associated with groundwater-level declines is stipulated as an “undesirable effect” in California’s Sustainable Groundwater Management Act (SGMA), and has been identified as a potential issue in San Diego, California, USA. The United States Geological Survey (USGS), the Sweetwater Authority, and the City of San Diego, undertook a cooperative study to better understand the hydromechanical response of the coastal aquifer system using Interferometric Synthetic Aperture Radar (InSAR) techniques. Three periods of interest were analyzed for this study that correspond to the periods before and after two substantial changes were made to the location and volume of pumpage: (1) April–August 2016 when groundwater levels and land surface elevation were relatively stable during normal pumping, (2) September 2016–May 2017 when groundwater levels recovered and the land surface uplifted during a period of substantially reduced pumping, (3) June 2017–October 2018 when groundwater levels declined and land subsidence occurred when pumpage resumed and expanded to new wells. Spatial and temporal characterization of the hydromechanical response to changes in pumpage is important for managing land subsidence. Further study using InSAR techniques, especially when combined with ground-based geodetic and monitoring-well networks, will provide water managers information to help effectively manage groundwater resources as stipulated in the SGMA.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of the International Association of Hydrological Sciences","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"Copernicus Publications","doi":"10.5194/piahs-382-45-2020","collaboration":"City of San Diego, Sweetwater Authority","usgsCitation":"Brandt, J.T., Sneed, M., and Danskin, W.R., 2020, Detection and measurement of land subsidence and uplift using interferometric synthetic aperture radar, San Diego, California, USA, 2016–2018, <i>in</i> Proceedings of the International Association of Hydrological Sciences, v. 382, p. 45-49, https://doi.org/10.5194/piahs-382-45-2020.","productDescription":"5 p.","startPage":"45","endPage":"49","ipdsId":"IP-111228","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":456989,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/piahs-382-45-2020","text":"Publisher Index Page"},{"id":374348,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","city":"San Diego","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -117.28179931640626,\n              32.565333160841035\n            ],\n            [\n              -117.04284667968749,\n              32.565333160841035\n            ],\n            [\n              -117.04284667968749,\n              32.75840715084112\n            ],\n            [\n              -117.28179931640626,\n              32.75840715084112\n            ],\n            [\n              -117.28179931640626,\n              32.565333160841035\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"382","noUsgsAuthors":false,"publicationDate":"2020-04-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Brandt, Justin T. 0000-0002-9397-6824 jbrandt@usgs.gov","orcid":"https://orcid.org/0000-0002-9397-6824","contributorId":157,"corporation":false,"usgs":true,"family":"Brandt","given":"Justin","email":"jbrandt@usgs.gov","middleInitial":"T.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":788014,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sneed, Michelle 0000-0002-8180-382X micsneed@usgs.gov","orcid":"https://orcid.org/0000-0002-8180-382X","contributorId":155,"corporation":false,"usgs":true,"family":"Sneed","given":"Michelle","email":"micsneed@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":788015,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Danskin, Wesley R. 0000-0001-8672-5501 wdanskin@usgs.gov","orcid":"https://orcid.org/0000-0001-8672-5501","contributorId":1034,"corporation":false,"usgs":true,"family":"Danskin","given":"Wesley","email":"wdanskin@usgs.gov","middleInitial":"R.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":788016,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70217223,"text":"70217223 - 2020 - The Missoula and Bonneville floods—A review of ice-age megafloods in the Columbia River basin","interactions":[],"lastModifiedDate":"2021-01-13T13:59:28.598323","indexId":"70217223","displayToPublicDate":"2020-04-22T07:51:58","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1431,"text":"Earth-Science Reviews","active":true,"publicationSubtype":{"id":10}},"title":"The Missoula and Bonneville floods—A review of ice-age megafloods in the Columbia River basin","docAbstract":"<p>The Channeled Scabland of eastern Washington State, USA, brought megafloods to the scientific forefront. A 30,000-km2 landscape of coulees and cataracts carved into the region’s loess-covered basalt attests to overwhelming volumes of energetic water. The scarred landscape, garnished by huge boulder bars and far-travelled ice-rafted erratics, spurred J Harlen Bretz’s vigorously disputed flood hypothesis in the 1920s. First known as the Spokane flood, it was rebranded the Missoula flood once understood that the water came from glacial Lake Missoula, formed when the Purcell Trench lobe of the last-glacial Cordilleran ice sheet dammed the Clark Fork valley in northwestern Idaho with ice a kilometer thick. Bretz’s flood evidence in the once-remote Channeled Scabland, widely seen and elaborated by the 1950s, eventually swayed consensus for cataclysmic flooding. Missoula flood questions then turned to some that continue today: how many? when? how big? what routes? what processes? </p><p>The Missoula floods passed through eastern Washington by a multitude of valleys, coulees and scabland tracts, some contemporaneously, some sequentially. Which routings and their timing depended on the positions of various lobes of the multi-pronged Cordilleran ice sheet and the erosional development of the channels themselves. The first floods mostly followed the big bend of Columbia valley looping through north-central Washington. But the south-advancing Okanogan ice lobe soon blocked that path, forming long-lasting glacial Lake Columbia in the impounded Columbia valley. Missoula floods into this lake were diverted south out of the Columbia valley and into eastern Washington coulees and scabland tracts. At least four floods entered Moses Coulee, but then as the Okanogan lobe advanced over and blocked the head of that coulee, more eastern paths took the water, including Grand Coulee and the Telford-Crab-Creek and Cheney-Palouse scabland tracts. Flood routing also depended on the erosion of the coulees. At some point, headward erosion of upper Grand Coulee lowered the divide saddle between the west-running Columbia valley and the deep and wide Grand Coulee heading southwest. Still uncertain is when this happened and the consequences with respect to the stage and extent of glacial Lake Columbia and to flood access to the other, higher, flood routes. Downstream, all flood routes converged onto Pasco Basin, flowed through Wallula Gap and the Columbia River Gorge into the Pacific Ocean, following submarine canyons and depositing sediment layers on abyssal plains. </p><p>Stratigraphic studies indicate dozens—likely more than a hundred—separate Missoula floods during the last glacial period. Over the length of the flood route, backwater areas and depositional basins preserve multiple flood beds, many of which are separated by signs of time, including volcanic ash layers and soil development in subaerial environments; and varve-like beds and pelagic mud layers in lacustrine and marine settings. Evidence also comes from the glacial Lake Missoula basin, where stratigraphy indicates dozens of filling and emptying cycles. Varve counts in conjunction of radiocarbon dating and paleomagnetic secular variation show the repeated filling-and-release cycles of glacial Lake Missoula had intervals possibly as long as 100 years early in the lake’s history but diminished to just one or two years for the last few floods. This behavior accords with jökulhlaup-style floods released by subglacial drainage from a self-dumping ice-dammed lake. But not yet clear is whether such a mechanism applies to all the floods or if some emptied more cataclysmically as hypothesized by some. </p><p>Radiocarbon dating of sparse organic materials remains key to defining flood chronology but has been lately bolstered by analyses of terrestrial cosmogenic nuclides and optically stimulated luminescence. Varve counts and paleomagnetic secular variation studies help to define durations and intervals represented by sequences of flood beds. The ~16 ka Mount St. Helens Set S tephra is commonly interbedded within flood deposits, enabling correlation of deposits among sites. Tephra from the 13.7–13.4 ka eruption of Glacier Peak overlies all glacial Lake Missoula and Missoula flood deposits, defining an end time. Overall conclusions are that glacial Lake Missoula was extant and producing floods for at least 3–4 ky during 20–14 ka. At least ~75 floods preceded Mount St Helens Set S, followed by 30 or more after the tephra fall. Most floods entered glacial Lake Columbia, impounded by the Okanogan lobe, for 2–5 ky between about 18.5 and 15 ka. Glacial Lake Columbia outlived Lake Missoula by &gt;200–400 yr but may have been born later since at least one flood came down the Columbia valley before the Okanogan ice lobe blocked the Columbia valley at 18.5–18 ka. The maximum extent of the Okanogan and Purcell Trench lobes, many Missoula floods, substantial erosion of upper Grand Coulee, and the widespread tephra falls from Mount St. Helens eruptions all happened about 17–15 ka. People, in the area since 16.6–15.3 ka, almost certainly witnessed the last of the Missoula floods and later large floods from other ice-dammed lakes in the Columbia River basin. </p><p>Quantitative flow analyses give peak discharge estimates and support understanding of erosional and depositional processes. The first flow assessments were simple cross-section calculations but recent assessments employ two-dimensional hydrodynamic models. The general finding is that emplacement of the maximum stage evidence requires about 20 million m3/s near the Lake Missoula outlet and about 5–15 million m3/s through Wallula Gap and downstream in the Columbia River Gorge. These hydraulic analyses raise still-unresolved questions regarding canyon erosion and possible additional water sources. </p><p>The large Pleistocene Bonneville flood entered the Columbia River system from the southeast from pluvial Lake Bonneville, the Pleistocene predecessor to Great Salt Lake in the eastern Great Basin. During the last glacial, the lake basin filled, covering &gt;50,000 km2 with 10,400 km3 of water before reaching its maximum possible stage governed by Red Rock Pass, the lowest divide separating the basin from the Snake River basin to the north. The overtopping lake rapidly incised 108–125 m into the Red Rock Pass outlet, spilling half of its total lake volume. G.K. Gilbert described the essential sequence in the 1870s, but the flood was mostly forgotten until the late 1950s when Harold Malde linked the spectacular scabland topography and bouldery “melon gravel” on the Snake River Plain to the Lake Bonneville overflow. The Bonneville flood appears to have been a singular event at about 18 ka. No evidence of multiple or pre-last-glacial spillovers has yet been found. Its total volume was about twice that of a maximum Lake Missoula flood yet its peak discharge was ~1 million m3/s, less than a tenth of the largest Missoula floods. Its comparatively simple flow path and much steadier flow make the Bonneville flood ideal for new studies of erosional and depositional processes. </p><p>At least two floods seem to have passed down the Columbia valley after the last of the Missoula floods, including a large flood about ~14 ka likely from cataclysmic demise of the thinning Okanogan ice lobe dam impounding glacial Lake Columbia. Floods from earlier glacial ages left scant yet clear evidence in the Channeled Scabland and Columbia valley. But their source, timing, and magnitudes are little understood. Some deposits are paleomagnetically reversed, thus older than ~800 ka. Last-glacial floods and perhaps older ones affected the Snake River Plain, some likely sourced in lakes dammed by alpine glaciers in central Idaho.</p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.earscirev.2020.103181","usgsCitation":"O'Connor, J., Baker, V.R., Waitt, R.B., Smith, L.N., Cannon, C.M., George, D.L., and Denlinger, R.P., 2020, The Missoula and Bonneville floods—A review of ice-age megafloods in the Columbia River basin: Earth-Science Reviews, v. 208, 103181, 51 p., https://doi.org/10.1016/j.earscirev.2020.103181.","productDescription":"103181, 51 p.","ipdsId":"IP-117652","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":456992,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://archimer.ifremer.fr/doc/00624/73634/","text":"External Repository"},{"id":382128,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho, Oregon, Washington","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -120.76171875,\n              45.73685954736049\n            ],\n            [\n              -116.4111328125,\n              45.73685954736049\n            ],\n            [\n              -116.4111328125,\n              48.31242790407178\n            ],\n            [\n              -120.76171875,\n              48.31242790407178\n            ],\n            [\n              -120.76171875,\n              45.73685954736049\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"208","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"O'Connor, Jim E. 0000-0002-7928-5883 oconnor@usgs.gov","orcid":"https://orcid.org/0000-0002-7928-5883","contributorId":140771,"corporation":false,"usgs":true,"family":"O'Connor","given":"Jim E.","email":"oconnor@usgs.gov","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":false,"id":808089,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Baker, Victor R.","contributorId":201141,"corporation":false,"usgs":false,"family":"Baker","given":"Victor","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":808090,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Waitt, Richard B. 0000-0002-6392-5604 waitt@usgs.gov","orcid":"https://orcid.org/0000-0002-6392-5604","contributorId":2343,"corporation":false,"usgs":true,"family":"Waitt","given":"Richard","email":"waitt@usgs.gov","middleInitial":"B.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":808091,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Smith, Larry N","contributorId":247679,"corporation":false,"usgs":false,"family":"Smith","given":"Larry","email":"","middleInitial":"N","affiliations":[{"id":49605,"text":"Montana Technological University","active":true,"usgs":false}],"preferred":false,"id":808092,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cannon, Charles M. 0000-0003-4136-2350 ccannon@usgs.gov","orcid":"https://orcid.org/0000-0003-4136-2350","contributorId":247680,"corporation":false,"usgs":true,"family":"Cannon","given":"Charles","email":"ccannon@usgs.gov","middleInitial":"M.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":808093,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"George, David L. 0000-0002-5726-0255 dgeorge@usgs.gov","orcid":"https://orcid.org/0000-0002-5726-0255","contributorId":3120,"corporation":false,"usgs":true,"family":"George","given":"David","email":"dgeorge@usgs.gov","middleInitial":"L.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":808094,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Denlinger, Roger P. 0000-0003-0930-0635 roger@usgs.gov","orcid":"https://orcid.org/0000-0003-0930-0635","contributorId":2679,"corporation":false,"usgs":true,"family":"Denlinger","given":"Roger","email":"roger@usgs.gov","middleInitial":"P.","affiliations":[{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":808095,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70209671,"text":"ofr20201023 - 2020 - Design and methods of the California stream quality assessment (CSQA), 2017","interactions":[],"lastModifiedDate":"2020-04-27T12:01:20.795249","indexId":"ofr20201023","displayToPublicDate":"2020-04-21T14:01:19","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":"2020-1023","displayTitle":"Design and Methods of the California Stream Quality Assessment (CSQA), 2017","title":"Design and methods of the California stream quality assessment (CSQA), 2017","docAbstract":"<p>During 2017, as part of the National Water-Quality Assessment Project, the U.S. Geological Survey conducted the California Stream Quality Assessment to investigate the quality of streams in the Central California Foothills and Coastal Mountains ecoregion, United States. The goal of the California Stream Quality Assessment study was to assess the health of wadeable streams in the region by characterizing multiple water-quality factors that are stressors to aquatic biota and by evaluating the relation between these stressors and biological indicators of stream health. Urbanization, agriculture, and modifications to streamflow are anthropogenic changes that affect water quality in the region; consequently, the study design primarily targeted sites and specific stressors associated with these activities. For the study, 85 stream sites were selected to represent the types and intensity of land use in the watershed; categories of site types were undeveloped, urban (low, medium, high), agriculture (low, high), and mixed (urban and agriculture). Most sites (about 70 percent) represent a gradient of urbanization from undeveloped to 99-percent urbanized. At most of the sites, streamgages or pressure transducers were used to monitor stream discharge and stage, as well as temperature. Water-quality samples were collected routinely at all sites and were analyzed for major ions, organic contaminants, nutrients, and suspended sediment. Sampling frequency varied on the basis of site type and location. Discrete water samples were collected weekly and generally 6 times per site, except for 11 undeveloped sites that were sampled only 4 times (during the last 4 weeks). Water sampling began at sites in the southern part of the study on March 13, 2017, and at sites in the northern part of the study on April 3, 2017. Passive samplers were deployed at most sites for measurement of polar organic contaminants (pesticides and pharmaceuticals). In May 2017, coincident with completion of water-quality sampling, an ecological survey was conducted at each site to assess benthic algal and macroinvertebrate communities and instream habitat. During the ecological surveys, a single composite streambed-sediment sample was collected for chemical analysis and toxicity testing. In addition, a few focused studies were done at subsets of sites, namely, measuring pesticides using small-volume automated samplers, measuring pesticides in biofilms, and sampling suspended sediments using passive samplers. This report describes the various study components and methods of the California Stream Quality Assessment, including measurements of water quality, sediment chemistry, habitat assessments, and ecological surveys, as well as procedures for sample analysis, quality assurance and quality control, and data management.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201023","collaboration":"National Water Quality Program","usgsCitation":"May, J.T., Nowell, L.H., Coles, J.F., Button, D.T., Bell, A.H., Qi, S.L., and Van Metre, P.C., 2020, Design and methods of the California stream quality assessment, 2017: U.S. Geological Survey Open-File Report 2020–1023, 88 p.,","productDescription":"Report: x, 88 p.; 1 Table","numberOfPages":"88","onlineOnly":"Y","ipdsId":"IP-105445","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":374128,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1023/ofr20201023.pdf","text":"Report","size":"6 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":374127,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1023/coverthb.jpg"},{"id":374197,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/of/2020/1023/ofr20201023_app_table_1.1.xlsx","text":"Table 1.1","size":"30 KB","linkFileType":{"id":3,"text":"xlsx"},"linkHelpText":" - Sampling matrix for the 85 sites used in the U.S. Geological Survey California Stream Quality Assessment in 2017."}],"country":"United States","state":"California","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -120.34423828125,\n              34.50655662164561\n            ],\n            [\n              -119.267578125,\n              34.95799531086792\n            ],\n            [\n              -121.4208984375,\n              37.78808138412046\n            ],\n            [\n              -122.10205078125,\n              39.14710270770074\n            ],\n            [\n              -122.25585937500001,\n              39.41922073655956\n            ],\n            [\n              -123.48632812499999,\n              38.85682013474361\n            ],\n            [\n              -122.67333984374999,\n              37.87485339352928\n            ],\n            [\n              -122.05810546875,\n              37.055177106660814\n            ],\n            [\n              -121.79443359375,\n              36.65079252503471\n            ],\n            [\n              -121.9482421875,\n              36.61552763134925\n            ],\n            [\n              -121.83837890625,\n              36.155617833818525\n            ],\n            [\n              -121.26708984374999,\n              35.585851593232356\n            ],\n            [\n              -120.58593749999999,\n              35.04798673426734\n            ],\n            [\n              -120.5419921875,\n              34.488447837809304\n            ],\n            [\n              -120.34423828125,\n              34.50655662164561\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":"2020-04-21","noUsgsAuthors":false,"publicationDate":"2020-04-21","publicationStatus":"PW","contributors":{"authors":[{"text":"May, Jason T. 0000-0002-5699-2112 jasonmay@usgs.gov","orcid":"https://orcid.org/0000-0002-5699-2112","contributorId":184174,"corporation":false,"usgs":true,"family":"May","given":"Jason T.","email":"jasonmay@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":787461,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nowell, Lisa H. 0000-0001-5417-7264 lhnowell@usgs.gov","orcid":"https://orcid.org/0000-0001-5417-7264","contributorId":490,"corporation":false,"usgs":true,"family":"Nowell","given":"Lisa","email":"lhnowell@usgs.gov","middleInitial":"H.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":787462,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Coles, James F. 0000-0002-1953-012X jcoles@usgs.gov","orcid":"https://orcid.org/0000-0002-1953-012X","contributorId":2239,"corporation":false,"usgs":true,"family":"Coles","given":"James","email":"jcoles@usgs.gov","middleInitial":"F.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":787463,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Button, Daniel T. 0000-0002-7479-884X dtbutton@usgs.gov","orcid":"https://orcid.org/0000-0002-7479-884X","contributorId":2084,"corporation":false,"usgs":true,"family":"Button","given":"Daniel","email":"dtbutton@usgs.gov","middleInitial":"T.","affiliations":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true},{"id":513,"text":"Ohio Water Science Center","active":true,"usgs":true},{"id":382,"text":"Michigan Water Science Center","active":true,"usgs":true}],"preferred":true,"id":787464,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bell, Amanda H. 0000-0002-7199-2145 ahbell@usgs.gov","orcid":"https://orcid.org/0000-0002-7199-2145","contributorId":1752,"corporation":false,"usgs":true,"family":"Bell","given":"Amanda","email":"ahbell@usgs.gov","middleInitial":"H.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":787465,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Qi, Sharon L. 0000-0001-7278-4498 slqi@usgs.gov","orcid":"https://orcid.org/0000-0001-7278-4498","contributorId":1130,"corporation":false,"usgs":true,"family":"Qi","given":"Sharon","email":"slqi@usgs.gov","middleInitial":"L.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true},{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":787466,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Van Metre, Peter C. 0000-0001-7564-9814","orcid":"https://orcid.org/0000-0001-7564-9814","contributorId":211144,"corporation":false,"usgs":true,"family":"Van Metre","given":"Peter","email":"","middleInitial":"C.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true},{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":true,"id":787467,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70211935,"text":"70211935 - 2020 - Biogeography and phylogeny of masting: Do global patterns fit functional hypotheses?","interactions":[],"lastModifiedDate":"2020-08-12T16:37:27.978771","indexId":"70211935","displayToPublicDate":"2020-04-21T11:26:05","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2863,"text":"New Phytologist","active":true,"publicationSubtype":{"id":10}},"title":"Biogeography and phylogeny of masting: Do global patterns fit functional hypotheses?","docAbstract":"<p>1) Interannual variability of seed crops (CVp) has profound consequences for plant populations and food webs, where high CVp is termed ‘masting’. Here we ask: is global variation in CVp better predicted by plant or habitat differences consistent with adaptive economies of scale, in which flower and seed benefits increase disproportionately during mast years; or to passive mechanisms, in which seed production responds to variation in resource availability associated with climate variability? </p><p>2) To address this question, we compiled a dataset for phylogenetic comparative analysis of long-term fruit/seed production for plants comprising 920 time-series spanning 311 plant species.</p><p> 3) Factors associated with both adaptive benefits of CVp (wind pollination and seed dispersal) and climatic variability (variability of summer precipitation) were among the best predictors of global variation in CVp. We observed a hump-shaped relationship between CVp and latitude and intermediate phylogenetic and geographic signals in CVp. </p><p>4) CVp is patterned non-randomly across the globe and over the plant tree of life, where high CVp is associated with species benefiting from economies of scale of seed or flower production and with species that experience variable rainfall over summer months when seeds usually mature.</p>","language":"English","publisher":"Wiley","doi":"10.1111/nph.16617","usgsCitation":"Pearse, I., LaMontagne, J., Lordon, M., Hipp, A., and Koenig, W.D., 2020, Biogeography and phylogeny of masting: Do global patterns fit functional hypotheses?: New Phytologist, v. 227, no. 5, p. 1557-1567, https://doi.org/10.1111/nph.16617.","productDescription":"11 p.","startPage":"1557","endPage":"1567","ipdsId":"IP-106437","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":456994,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/nph.16617","text":"Publisher Index Page"},{"id":437017,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9U7278U","text":"USGS data release","linkHelpText":"Data on interannual seed set variation, weather, and reproductive traits for global plants"},{"id":377406,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"227","issue":"5","noUsgsAuthors":false,"publicationDate":"2020-05-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Pearse, Ian S. 0000-0001-7098-0495","orcid":"https://orcid.org/0000-0001-7098-0495","contributorId":211154,"corporation":false,"usgs":true,"family":"Pearse","given":"Ian","middleInitial":"S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":795874,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"LaMontagne, Jalene M.","contributorId":223096,"corporation":false,"usgs":false,"family":"LaMontagne","given":"Jalene","middleInitial":"M.","affiliations":[{"id":36623,"text":"DePaul University","active":true,"usgs":false}],"preferred":false,"id":795875,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lordon, Michael","contributorId":228860,"corporation":false,"usgs":false,"family":"Lordon","given":"Michael","email":"","affiliations":[{"id":36623,"text":"DePaul University","active":true,"usgs":false}],"preferred":false,"id":795876,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hipp, Andrew","contributorId":219598,"corporation":false,"usgs":false,"family":"Hipp","given":"Andrew","email":"","affiliations":[{"id":37343,"text":"The Morton Arboretum","active":true,"usgs":false}],"preferred":false,"id":795877,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Koenig, Walter D.","contributorId":46255,"corporation":false,"usgs":false,"family":"Koenig","given":"Walter","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":795878,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70216404,"text":"70216404 - 2020 - FiCli, the Fish and Climate Change Database, informs climate adaptation and management for freshwater fishes","interactions":[],"lastModifiedDate":"2021-06-04T15:34:12.008748","indexId":"70216404","displayToPublicDate":"2020-04-21T09:03:28","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3907,"text":"Scientific Data","active":true,"publicationSubtype":{"id":10}},"title":"FiCli, the Fish and Climate Change Database, informs climate adaptation and management for freshwater fishes","docAbstract":"<div id=\"Abs1-section\" class=\"c-article-section\"><div id=\"Abs1-content\" class=\"c-article-section__content\"><p><span>Inland fishes provide important ecosystem services to communities worldwide and are especially vulnerable to the impacts of climate change. Fish respond to climate change in diverse and nuanced ways, which creates challenges for practitioners of fish conservation, climate change adaptation, and management. Although climate change is known to affect fish globally, a comprehensive online, public database of how climate change has impacted inland fishes worldwide and adaptation or management practices that may address these impacts does not exist. We conducted an extensive, systematic primary literature review to identify peer-reviewed journal publications describing projected and documented examples of climate change impacts on inland fishes. From this standardized&nbsp;</span><u>Fi</u><span>sh and&nbsp;</span><u>Cli</u><span>mate Change database, FiCli (pronounced fick-lee), researchers and managers can query fish families, species, response types, or geographic locations to obtain summary information on inland fish responses to climate change and recommended management actions. The FiCli database is updatable and provides access to comprehensive published information to inform inland fish conservation and adaptation planning in a changing climate.</span></p></div></div><div id=\"Abs2-section\" class=\"c-article-section\"><div id=\"Abs2-content\" class=\"c-article-section__content\"><br></div></div>","language":"English","publisher":"Nature","doi":"10.1038/s41597-020-0465-z","usgsCitation":"Krabbenhoft, T.J., Myers, B., Wong, J., Chu, C., Tingley, R.W., Falke, J.A., Kwak, T.J., Paukert, C.P., and Lynch, A., 2020, FiCli, the Fish and Climate Change Database, informs climate adaptation and management for freshwater fishes: Scientific Data, v. 7, 124, 6 p., https://doi.org/10.1038/s41597-020-0465-z.","productDescription":"124, 6 p.","ipdsId":"IP-114173","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":36940,"text":"National Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":456997,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41597-020-0465-z","text":"Publisher Index Page"},{"id":380533,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7","noUsgsAuthors":false,"publicationDate":"2020-04-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Krabbenhoft, Trevor J.","contributorId":176498,"corporation":false,"usgs":false,"family":"Krabbenhoft","given":"Trevor","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":804925,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Myers, Bonnie Jean Evaline 0000-0002-3170-2633","orcid":"https://orcid.org/0000-0002-3170-2633","contributorId":244910,"corporation":false,"usgs":true,"family":"Myers","given":"Bonnie Jean Evaline","affiliations":[{"id":36940,"text":"National Climate Adaptation Science Center","active":true,"usgs":true}],"preferred":true,"id":804924,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wong, Jesse","contributorId":244911,"corporation":false,"usgs":false,"family":"Wong","given":"Jesse","affiliations":[{"id":49017,"text":"Department of Environmental Science and Policy, George Mason University","active":true,"usgs":false}],"preferred":false,"id":804926,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Chu, Cindy","contributorId":176496,"corporation":false,"usgs":false,"family":"Chu","given":"Cindy","email":"","affiliations":[],"preferred":false,"id":804927,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Tingley, Ralph W.","contributorId":244912,"corporation":false,"usgs":false,"family":"Tingley","given":"Ralph","email":"","middleInitial":"W.","affiliations":[{"id":49018,"text":"Missouri Cooperative Fish and Wildlife Research Unit, The School of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":804928,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Falke, Jeffrey A. 0000-0002-6670-8250 jfalke@usgs.gov","orcid":"https://orcid.org/0000-0002-6670-8250","contributorId":5195,"corporation":false,"usgs":true,"family":"Falke","given":"Jeffrey","email":"jfalke@usgs.gov","middleInitial":"A.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":804929,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kwak, Thomas J. 0000-0002-0616-137X tkwak@usgs.gov","orcid":"https://orcid.org/0000-0002-0616-137X","contributorId":834,"corporation":false,"usgs":true,"family":"Kwak","given":"Thomas","email":"tkwak@usgs.gov","middleInitial":"J.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":804930,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Paukert, Craig P. 0000-0002-9369-8545 cpaukert@usgs.gov","orcid":"https://orcid.org/0000-0002-9369-8545","contributorId":147821,"corporation":false,"usgs":true,"family":"Paukert","given":"Craig","email":"cpaukert@usgs.gov","middleInitial":"P.","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":804931,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Lynch, Abigail 0000-0001-8449-8392","orcid":"https://orcid.org/0000-0001-8449-8392","contributorId":220490,"corporation":false,"usgs":true,"family":"Lynch","given":"Abigail","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":804932,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70215136,"text":"70215136 - 2020 - Post-fire management-scale trials of bacterial soil amendment MB906 show inconsistent control of invasive annual grasses","interactions":[],"lastModifiedDate":"2020-11-13T20:17:35.369323","indexId":"70215136","displayToPublicDate":"2020-04-21T07:51:50","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3228,"text":"Rangeland Ecology and Management","onlineIssn":"1551-5028","printIssn":"1550-7424","active":true,"publicationSubtype":{"id":10}},"title":"Post-fire management-scale trials of bacterial soil amendment MB906 show inconsistent control of invasive annual grasses","docAbstract":"<div id=\"abstracts\" class=\"Abstracts u-font-serif\"><div id=\"abs0001\" class=\"abstract author\"><div id=\"abss0001\"><p id=\"spara005\">Rangeland managers need tools to control invasive annual grasses, particularly following wildfire. We assessed responses of native and invasive/exotic grasses to the MB906 soil amendment containing live cultures of a purportedly weed-suppressive strain of the bacterium<span>&nbsp;</span><i>Pseudomonas fluorescens</i><span>&nbsp;</span>(“WSB”). MB906 was applied alone and in combination with the pre-emergent herbicide imazapic on &gt;3000 ha across three sagebrush-steppe landscapes burned several months prior. Replicate plots of each treatment type were established and plant cover was measured in the following three years. Cover of invasive-annual grasses (“IAG”) was not responsive to MB906 when all IAG species were considered (“IAG-All”). However, MB906 led to a 54% reduction in the IAG's that were previously reported to be controlled by WSB (“IAG-Target”) in the second year following application (IAG-Target = cheatgrass,<span>&nbsp;</span><i>Bromus tectorum</i><span>&nbsp;</span>and medusahead,<span>&nbsp;</span><i>Taeniatherum caput-medusae;</i><span>&nbsp;</span>IAG-All also includes<span>&nbsp;</span><i>Vulpia myuros</i><span>&nbsp;</span>and<span>&nbsp;</span><i>Bromus arvensis</i>). MB906 reduced the effectiveness of co-applied imazapic: Imazapic alone reduced IAG-All by 83% and 68% in years 1 and 2, respectively, while imazapic+MB906 reduced IAG-All by 48% and 38% in years 1 and 2, respectively, across all landscapes, and a similar response pattern was observed for IAG-Target. Perennial grass cover was unaffected by the treatments except where it increased 4-fold in response to imazapic applied at a high rate (0.140 kg a.i. ha<sup>−1</sup>) in one of the landscapes. Tank mixing MB906 and herbicide may have lessened the biological activity of the herbicide by altering the pH or mineral content of the spray solution or by direct metabolism of the herbicide by the bacteria. These results do not provide strong support for MB906 as a tool for annual grass control, though they suggest further investigation may be warranted.</p></div></div></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.rama.2020.03.005","usgsCitation":"Lazarus, B., Germino, M., Brabec, M., Peterson, L., Walker, R.N., and Moser, A., 2020, Post-fire management-scale trials of bacterial soil amendment MB906 show inconsistent control of invasive annual grasses: Rangeland Ecology and Management, v. 73, no. 6, p. 741-748, https://doi.org/10.1016/j.rama.2020.03.005.","productDescription":"8 p.","startPage":"741","endPage":"748","ipdsId":"IP-111914","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":456999,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.rama.2020.03.005","text":"Publisher Index Page"},{"id":379219,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"73","issue":"6","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Lazarus, Brynne E. 0000-0002-6352-486X","orcid":"https://orcid.org/0000-0002-6352-486X","contributorId":242732,"corporation":false,"usgs":true,"family":"Lazarus","given":"Brynne E.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":800973,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Germino, Matthew 0000-0001-6326-7579","orcid":"https://orcid.org/0000-0001-6326-7579","contributorId":218007,"corporation":false,"usgs":true,"family":"Germino","given":"Matthew","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":800974,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brabec, Martha mbrabec@usgs.gov","contributorId":242857,"corporation":false,"usgs":false,"family":"Brabec","given":"Martha","email":"mbrabec@usgs.gov","affiliations":[{"id":37341,"text":"City of Boise","active":true,"usgs":false}],"preferred":false,"id":800975,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Peterson, Logan","contributorId":242860,"corporation":false,"usgs":false,"family":"Peterson","given":"Logan","email":"","affiliations":[{"id":36224,"text":"Idaho Department of Fish and Game","active":true,"usgs":false}],"preferred":false,"id":800976,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Walker, Ryan N","contributorId":242863,"corporation":false,"usgs":false,"family":"Walker","given":"Ryan","email":"","middleInitial":"N","affiliations":[{"id":36224,"text":"Idaho Department of Fish and Game","active":true,"usgs":false}],"preferred":false,"id":800977,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Moser, Ann","contributorId":201657,"corporation":false,"usgs":false,"family":"Moser","given":"Ann","affiliations":[{"id":36224,"text":"Idaho Department of Fish and Game","active":true,"usgs":false}],"preferred":false,"id":800978,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70209777,"text":"70209777 - 2020 - Mapping perceived social values to support a respondent-defined restoration economy: Case study in southeastern Arizona, USA","interactions":[],"lastModifiedDate":"2020-04-30T13:31:57.437681","indexId":"70209777","displayToPublicDate":"2020-04-21T07:47:35","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":686,"text":"Air, Soil and Water Research","active":true,"publicationSubtype":{"id":10}},"title":"Mapping perceived social values to support a respondent-defined restoration economy: Case study in southeastern Arizona, USA","docAbstract":"Investment in conservation and ecological restoration depends on various socioeconomic factors and the social license for these activities. Our study demonstrates a method for targeting management of ecosystem services based on social values, identified by respondents through a collection of social survey data. We applied the Social Values for Ecosystem Services (SolVES) geographic information systems (GIS)-based tool in the Sonoita Creek watershed, Arizona, to map social values across the watershed. The survey focused on how respondents engage with the landscape, including through their ranking of 12 social values (eg, recreational, economic, or aesthetic value) and their placement of points on a map to identify their associations with the landscape. Additional information was elicited regarding how respondents engaged with water and various land uses, as well as their familiarity with restoration terminology. Results show how respondents perceive benefits from the natural environment. Specifically, maps of social values on the landscape show high social value along streamlines. Life-sustaining services, biological diversity, and aesthetics were the respondents’ highest rated social values. Land surrounding National Forest and private lands had lower values than conservation-based and state-owned areas, which we associate with landscape features. Results can inform watershed management by allowing managers to consider social values when prioritizing restoration or conservation investments.","language":"English","publisher":"SAGE Journals","doi":"10.1177/1178622120913318","collaboration":"","usgsCitation":"Petrakis, R., Norman, L., Lysaght, O., Sherrouse, B.C., Semmens, D.J., Bagstad, K.J., and Pritzlaff, R., 2020, Mapping perceived social values to support a respondent-defined restoration economy: Case study in southeastern Arizona, USA: Air, Soil and Water Research, v. 13, https://doi.org/10.1177/1178622120913318.","productDescription":"16 p.","startPage":"","ipdsId":"IP-112256","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":457002,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1177/1178622120913318","text":"Publisher Index Page"},{"id":437018,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P98B4B1X","text":"USGS data release","linkHelpText":"Perceived Social Value of the Sonoita Creek Watershed using the Social Values for Ecosystem Services (SolVES) Tool, Arizona, U.S.A."},{"id":374311,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -111.42333984375,\n              31.287939892641734\n            ],\n            [\n              -110.63232421875,\n              31.287939892641734\n            ],\n            [\n              -110.63232421875,\n              31.765537409484374\n            ],\n            [\n              -111.42333984375,\n              31.765537409484374\n            ],\n            [\n              -111.42333984375,\n              31.287939892641734\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"13","noUsgsAuthors":false,"publicationDate":"2020-04-21","publicationStatus":"PW","contributors":{"editors":[{"text":"Lysaght, Oliver","contributorId":224361,"corporation":false,"usgs":false,"family":"Lysaght","given":"Oliver","email":"","affiliations":[{"id":40864,"text":"Borderlands Restoration Network and London School of Economics and Political Science","active":true,"usgs":false}],"preferred":false,"id":787965,"contributorType":{"id":2,"text":"Editors"},"rank":3},{"text":"Sherrouse, Benson C. 0000-0002-5102-5895 bcsherrouse@usgs.gov","orcid":"https://orcid.org/0000-0002-5102-5895","contributorId":2445,"corporation":false,"usgs":true,"family":"Sherrouse","given":"Benson","email":"bcsherrouse@usgs.gov","middleInitial":"C.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":787966,"contributorType":{"id":2,"text":"Editors"},"rank":4},{"text":"Semmens, Darius J. 0000-0001-7924-6529","orcid":"https://orcid.org/0000-0001-7924-6529","contributorId":64201,"corporation":false,"usgs":true,"family":"Semmens","given":"Darius J.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":787967,"contributorType":{"id":2,"text":"Editors"},"rank":5},{"text":"Bagstad, Kenneth J. 0000-0001-8857-5615 kjbagstad@usgs.gov","orcid":"https://orcid.org/0000-0001-8857-5615","contributorId":3680,"corporation":false,"usgs":true,"family":"Bagstad","given":"Kenneth","email":"kjbagstad@usgs.gov","middleInitial":"J.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":787968,"contributorType":{"id":2,"text":"Editors"},"rank":6},{"text":"Pritzlaff, Richard","contributorId":224362,"corporation":false,"usgs":false,"family":"Pritzlaff","given":"Richard","email":"","affiliations":[{"id":40865,"text":"The Biophilia Foundation","active":true,"usgs":false}],"preferred":false,"id":787969,"contributorType":{"id":2,"text":"Editors"},"rank":7}],"authors":[{"text":"Petrakis, Roy E. 0000-0001-8932-077X rpetrakis@usgs.gov","orcid":"https://orcid.org/0000-0001-8932-077X","contributorId":174623,"corporation":false,"usgs":true,"family":"Petrakis","given":"Roy","email":"rpetrakis@usgs.gov","middleInitial":"E.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":787963,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Norman, Laura M. 0000-0002-3696-8406","orcid":"https://orcid.org/0000-0002-3696-8406","contributorId":203300,"corporation":false,"usgs":true,"family":"Norman","given":"Laura M.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":787964,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lysaght, Oliver","contributorId":224361,"corporation":false,"usgs":false,"family":"Lysaght","given":"Oliver","email":"","affiliations":[{"id":40864,"text":"Borderlands Restoration Network and London School of Economics and Political Science","active":true,"usgs":false}],"preferred":false,"id":787993,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sherrouse, Benson C. 0000-0002-5102-5895 bcsherrouse@usgs.gov","orcid":"https://orcid.org/0000-0002-5102-5895","contributorId":2445,"corporation":false,"usgs":true,"family":"Sherrouse","given":"Benson","email":"bcsherrouse@usgs.gov","middleInitial":"C.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":787994,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Semmens, Darius J. 0000-0001-7924-6529 dsemmens@usgs.gov","orcid":"https://orcid.org/0000-0001-7924-6529","contributorId":1714,"corporation":false,"usgs":true,"family":"Semmens","given":"Darius","email":"dsemmens@usgs.gov","middleInitial":"J.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":787995,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bagstad, Kenneth J. 0000-0001-8857-5615 kjbagstad@usgs.gov","orcid":"https://orcid.org/0000-0001-8857-5615","contributorId":3680,"corporation":false,"usgs":true,"family":"Bagstad","given":"Kenneth","email":"kjbagstad@usgs.gov","middleInitial":"J.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":787996,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Pritzlaff, Richard","contributorId":224362,"corporation":false,"usgs":false,"family":"Pritzlaff","given":"Richard","email":"","affiliations":[{"id":40865,"text":"The Biophilia Foundation","active":true,"usgs":false}],"preferred":false,"id":787997,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70223193,"text":"70223193 - 2020 - Understanding sportsperson retention and reactivation through license purchasing behavior","interactions":[],"lastModifiedDate":"2021-08-17T12:38:14.859094","indexId":"70223193","displayToPublicDate":"2020-04-21T07:36:50","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3779,"text":"Wildlife Society Bulletin","onlineIssn":"1938-5463","printIssn":"0091-7648","active":true,"publicationSubtype":{"id":10}},"title":"Understanding sportsperson retention and reactivation through license purchasing behavior","docAbstract":"<div class=\"abstract-group\"><div class=\"article-section__content en main\"><p>Most state and provincial fish and wildlife agencies have access to important information about patterns in sportsperson participation through their license databases. Using transaction data from Nebraska Game and Parks Commission's electronic hunting and fishing license system, we tracked license purchases of Nebraska, USA, resident license holders in 2010 through 2017. We categorized sportspersons by gender and yearly purchases as hunting only (Hunter), fishing only (Angler), a combination of hunting and fishing (Hunter–Angler), or no purchases (Inactive). The probability of movement among active sportsperson groups was limited and varied little based on initial group participation. The Angler group had the greatest probability of an individual transitioning to the Inactive group (females = 0.39; males = 0.33). The Hunter–Angler group had the greatest probability of an individual remaining within the same group (females = 0.65; males = 0.76). There was a relatively low probability of an individual in the Hunter group moving to the Angler group and vice versa (≤0.02). The sportsperson population is dynamic and understanding patterns of sportsperson participation is important for the future of fish and wildlife management in North America. Using data readily available to most fish and wildlife agencies has the potential to significantly improve our understanding of hunter and angler participation and aid management agencies and conservation organizations in the development of more effective strategies for managing sportspersons. © 2020 The Wildlife Society.</p></div></div>","language":"English","publisher":"Wiley","doi":"10.1002/wsb.1088","usgsCitation":"Hinrichs, M., Price, N.B., Gruntorad, M., Pope, K.L., Fontaine, J.J., and Chizinski, C.J., 2020, Understanding sportsperson retention and reactivation through license purchasing behavior: Wildlife Society Bulletin, v. 44, no. 2, p. 383-390, https://doi.org/10.1002/wsb.1088.","productDescription":"8 p.","startPage":"383","endPage":"390","ipdsId":"IP-100623","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":499921,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doaj.org/article/d2412cfe2d4f4ba3b3b77d53b20c9375","text":"External Repository"},{"id":387980,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"44","issue":"2","noUsgsAuthors":false,"publicationDate":"2020-04-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Hinrichs, M.P.","contributorId":264315,"corporation":false,"usgs":false,"family":"Hinrichs","given":"M.P.","email":"","affiliations":[{"id":36892,"text":"University of Nebraska","active":true,"usgs":false}],"preferred":false,"id":821328,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Price, Nathaniel B.","contributorId":264316,"corporation":false,"usgs":false,"family":"Price","given":"Nathaniel","email":"","middleInitial":"B.","affiliations":[{"id":36892,"text":"University of Nebraska","active":true,"usgs":false}],"preferred":false,"id":821329,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gruntorad, M.P.","contributorId":264317,"corporation":false,"usgs":false,"family":"Gruntorad","given":"M.P.","affiliations":[{"id":36892,"text":"University of Nebraska","active":true,"usgs":false}],"preferred":false,"id":821330,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pope, Kevin L. 0000-0003-1876-1687 kpope@usgs.gov","orcid":"https://orcid.org/0000-0003-1876-1687","contributorId":1574,"corporation":false,"usgs":true,"family":"Pope","given":"Kevin","email":"kpope@usgs.gov","middleInitial":"L.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":821331,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fontaine, Joseph J. 0000-0002-7639-9156 jfontaine@usgs.gov","orcid":"https://orcid.org/0000-0002-7639-9156","contributorId":3820,"corporation":false,"usgs":true,"family":"Fontaine","given":"Joseph","email":"jfontaine@usgs.gov","middleInitial":"J.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":821332,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Chizinski, C. J.","contributorId":243358,"corporation":false,"usgs":false,"family":"Chizinski","given":"C.","email":"","middleInitial":"J.","affiliations":[{"id":36892,"text":"University of Nebraska","active":true,"usgs":false}],"preferred":false,"id":821333,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70209750,"text":"70209750 - 2020 - Biological control of Aedes mosquito larvae with carnivorous aquatic plant, Utricularia macrorhiza","interactions":[],"lastModifiedDate":"2020-04-28T12:32:47.508801","indexId":"70209750","displayToPublicDate":"2020-04-21T07:22:04","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3010,"text":"Parasites & Vectors","printIssn":"1756-3305","active":true,"publicationSubtype":{"id":10}},"title":"Biological control of Aedes mosquito larvae with carnivorous aquatic plant, Utricularia macrorhiza","docAbstract":"<p><strong>Background</strong><br>Biological controls with predators of larval mosquito vectors have historically focused almost exclusively on insectivorous animals, with few studies examining predatory plants as potential larvacidal agents. In this study, we experimentally evaluate a generalist plant predator of North America, Utricularia macrorhiza, the common bladderwort, and evaluate its larvacidal efficiency for the mosquito vectors Aedes aegypti and Aedes albopictus in no-choice, laboratory experiments. We sought to determine first, whether U. macrorhiza is a competent predator of container-breeding mosquitoes, and second, its predation efficiency for early and late instar larvae of each mosquito species. </p><p><strong>Methods</strong><br>Newly hatched, first instar Aedes albopictus and Aedes aegypti larvae were separately exposed in cohorts of 10 to field collected U. macrorhiza cuttings. Data on development time and larval survival were collected on a daily basis to ascertain the effectiveness of U. macrorhiza as a larval predator. Survival models were used to assess differences in larval survival between cohorts that were exposed to U. macrorhiza and those that were not. A permutation analysis was used to investigate whether storing U. macrorhiza in laboratory conditions for extended periods of time (1 month vs. 6 months) affected its predation efficiency. </p><p><strong>Results</strong><br>Our results indicated a 100% and 95% reduction of survival of Ae. aegypti and Ae. albopictus larvae respectively, in the presence of U. macrorhiza relative to controls within five days, with peak larvacidal efficiency in plant cuttings from ponds collected in August. Utricularia macrorhiza cuttings, which were prey-deprived, and maintained in laboratory conditions for 6 months were more effective larval predators than cuttings, which were maintained prey-free for 1 month. </p><p><strong>Conclusions</strong><br>Due to the combination of high predation efficiency and the unique biological feature of facultative predation, we suggest that U. macrorhiza warrants further development as a method for larval mosquito control.</p>","language":"English","publisher":"BMC","doi":"10.1186/s13071-020-04084-4","collaboration":"","usgsCitation":"Couret, J., Notarangelo, M., Veera, S., LeClaire-Conway, N., Ginsberg, H., and LeBrun, R.A., 2020, Biological control of Aedes mosquito larvae with carnivorous aquatic plant, Utricularia macrorhiza: Parasites & Vectors, v. 13, https://doi.org/10.1186/s13071-020-04084-4.","productDescription":"208, 11 p.","startPage":"","ipdsId":"IP-114930","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":457006,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s13071-020-04084-4","text":"Publisher Index Page"},{"id":374309,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Rhode Island","county":"Washington 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,{"id":70209789,"text":"70209789 - 2020 - Novel insights into serodiagnosis and epidemiology of Erysipelothrix rhusiopathiae, a newly recognized pathogen in muskoxen (Ovibos moschatus)","interactions":[],"lastModifiedDate":"2020-04-29T12:24:15.804534","indexId":"70209789","displayToPublicDate":"2020-04-21T07:19:11","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Novel insights into serodiagnosis and epidemiology of Erysipelothrix rhusiopathiae, a newly recognized pathogen in muskoxen (Ovibos moschatus)","docAbstract":"Muskoxen are a key species of Arctic ecosystems and are important for food security and\nsocio-economic well-being of many Indigenous communities in the Arctic and Subarctic.\nBetween 2009 and 2014, the bacterium Erysipelothrix rhusiopathiae was isolated for the\nfirst time in this species in association with multiple mortality events in Canada and Alaska,\nraising questions regarding the spatiotemporal occurrence of the pathogen and its potential\nimpact on muskox populations.","language":"English","publisher":"PLoS ONE","doi":"10.1371/journal.pone.0231724","collaboration":"","usgsCitation":"Mavrot, F., Orsel, K., Hutchins, W., Adams, L., Beckmen, K., Blake, J., Checkley, S., Davison, T., Di Francesco, J., Elkin, B., Leclerc, L., Schneider, A., Tomaselli, M., and Kutz, S., 2020, Novel insights into serodiagnosis and epidemiology of Erysipelothrix rhusiopathiae, a newly recognized pathogen in muskoxen (Ovibos moschatus): PLoS ONE, v. 15, no. 4, e0231724, 14 p., https://doi.org/10.1371/journal.pone.0231724.","productDescription":"e0231724, 14 p.","ipdsId":"IP-113038","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":457009,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index 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W.","contributorId":224374,"corporation":false,"usgs":false,"family":"Hutchins","given":"W.","email":"","affiliations":[{"id":40870,"text":"University of Calgary, Alberta","active":true,"usgs":false}],"preferred":false,"id":788025,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Adams, Layne G. 0000-0001-6212-2896 ladams@usgs.gov","orcid":"https://orcid.org/0000-0001-6212-2896","contributorId":2776,"corporation":false,"usgs":true,"family":"Adams","given":"Layne G.","email":"ladams@usgs.gov","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":788026,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Beckmen, K.","contributorId":224375,"corporation":false,"usgs":false,"family":"Beckmen","given":"K.","affiliations":[{"id":7058,"text":"Alaska Department of Fish and Game","active":true,"usgs":false}],"preferred":false,"id":788027,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Blake, 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,{"id":70229339,"text":"70229339 - 2020 - Reply to Craine: Bison redefine what it means to move to find food","interactions":[],"lastModifiedDate":"2022-03-04T12:58:33.831488","indexId":"70229339","displayToPublicDate":"2020-04-21T06:55:38","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7587,"text":"PNAS - Proceedings of the National Academy of Sciences of the United States of America","active":true,"publicationSubtype":{"id":10}},"title":"Reply to Craine: Bison redefine what it means to move to find food","docAbstract":"<p>No abstract available.</p>","language":"English","publisher":"PNAS","doi":"10.1073/pnas.2000713117","usgsCitation":"Geremia, C., Merkle, J., White, P.J., and Kauffman, M., 2020, Reply to Craine: Bison redefine what it means to move to find food: PNAS - Proceedings of the National Academy of Sciences of the United States of America, v. 117, no. 17, 2 p., https://doi.org/10.1073/pnas.2000713117.","productDescription":"2 p.","ipdsId":"IP-118446","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":457010,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/7196808","text":"Publisher Index Page"},{"id":396741,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"117","issue":"17","noUsgsAuthors":false,"publicationDate":"2020-04-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Geremia, Chris","contributorId":167003,"corporation":false,"usgs":false,"family":"Geremia","given":"Chris","email":"","affiliations":[],"preferred":false,"id":837107,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Merkle, Jerod A.","contributorId":287300,"corporation":false,"usgs":false,"family":"Merkle","given":"Jerod A.","affiliations":[{"id":40829,"text":"uwy","active":true,"usgs":false}],"preferred":false,"id":837106,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"White, P. J.","contributorId":287825,"corporation":false,"usgs":false,"family":"White","given":"P.","email":"","middleInitial":"J.","affiliations":[{"id":36245,"text":"NPS","active":true,"usgs":false}],"preferred":false,"id":837105,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kauffman, Matthew J. 0000-0003-0127-3900","orcid":"https://orcid.org/0000-0003-0127-3900","contributorId":202921,"corporation":false,"usgs":true,"family":"Kauffman","given":"Matthew","middleInitial":"J.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":837108,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70209199,"text":"sim3455 - 2020 - Potentiometric surface and hydrologic conditions of the South Coast aquifer, Santa Isabel area, Puerto Rico, March–April, 2014","interactions":[],"lastModifiedDate":"2020-05-07T10:45:27.668534","indexId":"sim3455","displayToPublicDate":"2020-04-21T06:42:53","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3455","displayTitle":"Potentiometric Surface and Hydrologic Conditions of the South Coast Aquifer, Santa Isabel Area, Puerto Rico, March–April, 2014","title":"Potentiometric surface and hydrologic conditions of the South Coast aquifer, Santa Isabel area, Puerto Rico, March–April, 2014","docAbstract":"<p>A potentiometric surface map of the South Coast aquifer near Santa Isabel, Puerto Rico, was created from data collected during a synoptic survey of groundwater levels at 55 wells from March 31 to April 17, 2014. Measured groundwater level values ranged from −22.8 to 185.4 feet above mean sea level. During the study period, cumulative rainfall of 0.65 inch was recorded in the study area. Measurements of instantaneous streamflow at 15 locations in streams and irrigation canals, and locations of irrigation ponds, provide additional information about the hydrologic setting. Results of the study indicate a cone of depression was present near the center and eastern parts of the Santa Isabel area of southern Puerto Rico, and a small, deeper cone of depression existed west of Santa Isabel and Rio Coamo. These cones of depression represent areas where the potentiometric surface was below mean sea level. The long-term persistence of such conditions could result in seawater intrusion and an increase in concentrations of total dissolved solids within the South Coast aquifer.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3455","collaboration":"Prepared in cooperation with the Puerto Rico Department of Natural and Environmental Resources","usgsCitation":"Ramos, F.A., and Santiago, A.A., 2020, Potentiometric surface and hydrologic conditions of the South Coast aquifer, Santa Isabel area, Puerto Rico, March–April, 2014: U.S. Geological Survey Scientific Investigations Map 3455, 4 p., 1 sheet, https://doi.org/10.3133/sim3455.","productDescription":"Pamphlet: vi, 4 p.; Sheet: 35.68 inches x 28.17 inches; Data Release","numberOfPages":"14","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-064406","costCenters":[{"id":27821,"text":"Caribbean-Florida Water Science Center","active":true,"usgs":true}],"links":[{"id":374025,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7NS0STQ","text":"USGS data release","linkHelpText":"Data and shapefiles for the potentiometric surface of the South Coast aquifer and hydrologic conditions in the Santa Isabel area, Puerto Rico, March–April 2014"},{"id":374019,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3455/coverthb.jpg"},{"id":374021,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3455/sim3455.pdf","text":"Pamphlet","size":"350 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3455 Pamphlet"},{"id":374022,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3455/sim3455_sheet.pdf","text":"Sheet 1—","size":"4.07 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3455 Sheet","linkHelpText":"Potentiometric Surface and Hydrologic Conditions of the South Coast Aquifer, Santa Isabel Area, Puerto Rico, March–April, 2014"}],"country":"United States","state":"Puerto Rico","otherGeospatial":"Santa Isabel Area","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -66.4779281616211,\n              17.932682319509986\n            ],\n            [\n              -66.29854202270508,\n              17.932682319509986\n            ],\n            [\n              -66.29854202270508,\n              18.029995361346103\n            ],\n            [\n              -66.4779281616211,\n              18.029995361346103\n            ],\n            [\n              -66.4779281616211,\n              17.932682319509986\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","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>Methods of Investigation</li><li>Hydrologic Conditions and the Estimated Potentiometric Surface</li><li>Summary and Conclusions</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"publishedDate":"2020-04-21","noUsgsAuthors":false,"publicationDate":"2020-04-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Ramos, Felix A. 0000-0002-0924-3231","orcid":"https://orcid.org/0000-0002-0924-3231","contributorId":223530,"corporation":false,"usgs":true,"family":"Ramos","given":"Felix","email":"","middleInitial":"A.","affiliations":[{"id":27821,"text":"Caribbean-Florida Water Science Center","active":true,"usgs":true}],"preferred":true,"id":785357,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Santiago, Alex A. 0000-0002-4067-8022","orcid":"https://orcid.org/0000-0002-4067-8022","contributorId":223531,"corporation":false,"usgs":false,"family":"Santiago","given":"Alex","email":"","middleInitial":"A.","affiliations":[{"id":38734,"text":"former employee","active":true,"usgs":false}],"preferred":false,"id":785358,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70211823,"text":"70211823 - 2020 - If you build it and they come, will they stay? Maturation of constructed fish spawning reefs in the St. Clair-Detroit River System","interactions":[],"lastModifiedDate":"2020-08-07T22:15:05.735136","indexId":"70211823","displayToPublicDate":"2020-04-20T17:10:43","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1454,"text":"Ecological Engineering","active":true,"publicationSubtype":{"id":10}},"title":"If you build it and they come, will they stay? Maturation of constructed fish spawning reefs in the St. Clair-Detroit River System","docAbstract":"<p><span>Constructed rock reefs have been used to remediate spawning habitat for Lake Sturgeon (</span><i>Acipenser fulvescens</i><span>) and other lithophilic spawning fishes in the St. Clair-Detroit River System, North America. Early projects used a cross-channel design and species-specific metrics (e.g., proximity to historical spawning locations) to guide reef placement. However, the Middle Channel Reefs and portions of other early projects were compromised by fine sediment accumulation. Therefore, geomorphological criteria were considered in siting reefs constructed after 2013 to avoid sediment sources and improve the likelihood of successful reef function. To evaluate the effectiveness of the revised placement process, we quantified physical maturation of constructed reefs using annual side-scan and down-looking sonar surveys beginning in 2014 and underwater video surveys beginning in 2015. Reef areas and hardness were measured from sonar surveys and underwater video was used to quantify surficial sediment composition. Size and hardness of reefs developed using geomorphological criteria decreased with time, but at rates slower than what was observed at the Middle Channel Reefs. Sediment composition of the reefs remained similar through 2017 and prevalence of reef rock was high, except at Hart's Light Reef, where dreissenid mussel shells composed 32% of the surficial substrate by age three. However, accumulation of fine sediments was documented at all reefs in 2018. Despite using geomorphic criteria to identify areas most suitable for reef construction, reef sediment composition has changed, and future reef restoration projects could benefit by incorporating methods for maintenance, in addition to using geomorphic criteria, to identify restoration sites.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecoleng.2020.105837","usgsCitation":"Fischer, J., Roseman, E., Mayer, C., and Wills, T., 2020, If you build it and they come, will they stay? 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,{"id":70209640,"text":"fs20203022 - 2020 - Nature’s Notebook-A tool for recording the timing of seasonal activity of plants and animals","interactions":[],"lastModifiedDate":"2020-04-21T14:25:37.241199","indexId":"fs20203022","displayToPublicDate":"2020-04-20T13:15:00","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":"2020-3022","displayTitle":"<em>Nature’s Notebook</em>—A Tool for Recording the Timing of Seasonal Activity of Plants and Animals","title":"Nature’s Notebook-A tool for recording the timing of seasonal activity of plants and animals","docAbstract":"<p><i>Nature's Notebook</i> is a customizable program used by individual observers and Federal Government partners to document patterns in phenology—the timing of seasonal activity of plants and animals over the course of the calendar year. The USA National Phenology Network (USA-NPN) established <i>Nature's Notebook</i> in 2009 to create a standard approach for collecting phenology data on plants and animals across the country. Currently, about half of the data are submitted by independent backyard observers at individual sites and half are submitted by groups of participants as part of a Local Phenology Program. With support from the U.S. Geological Survey, the USA-NPN collects, organizes, and shares data on phenology. 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Traditional streamgaging requires sensors be deployed in the water column; however, near-field remote sensing has the potential to transform streamgaging operations through non-contact methods in the U.S. Geological Survey (USGS) and other agencies around the world. To differentiate from satellite or high-altitude platforms, near-field remote sensing is conducted from fixed platforms such as bridges and cable stays. Radar gages were collocated with 10 USGS streamgages in river reaches of varying hydrologic and hydraulic characteristics, where basin size ranged from 381 to 66,200 square kilometers. Radar-derived mean-channel (mean) velocity and discharge were computed using the probability concept and were compared to conventional instantaneous measurements and time series. To test the efficacy of near-field methods, radars were deployed for extended periods of time to capture a range of hydraulic conditions and environmental factors. During the operational phase, continuous time series of surface velocity, radar-derived discharge, and stage-discharge were recorded, computed, and transmitted contemporaneously and continuously in real time every 5 to 15 min. Minimum and maximum surface velocities ranged from 0.30 to 3.84 m per second (m/s); minimum and maximum radar-derived discharges ranged from 0.17 to 4890 cubic meters per second (m</span><sup>3</sup><span>/s); and minimum and maximum stage-discharge ranged from 0.12 to 4950 m</span><sup>3</sup><span>/s. Comparisons between radar and stage-discharge time series were evaluated using goodness-of-fit statistics, which provided a measure of the utility of the probability concept to compute discharge from a singular surface velocity and cross-sectional area relative to conventional methods. Mean velocity and discharge data indicate that velocity radars are highly correlated with conventional methods and are a viable near-field remote sensing technology that can be operationalized to deliver real-time surface velocity, mean velocity, and discharge.&nbsp;</span></p>","language":"English","publisher":"MDPI","doi":"10.3390/rs12081296","usgsCitation":"Fulton, J.W., Mason, C.A., Eggleston, J., Nicotra, M.J., Chiu, C., Henneberg, M.F., Best, H., Cederberg, J., Holnbeck, S.R., Lotspeich, R.R., Laveau, C., Moramarco, T., Jones, M.E., Gourley, J.J., and Wasielewski, D., 2020, Near-field remote sensing of surface velocity and river discharge using radars and the probability concept at 10 USGS streamgages: Remote Sensing, v. 12, no. 8, 1296, 28 p., https://doi.org/10.3390/rs12081296.","productDescription":"1296, 28 p.","ipdsId":"IP-116229","costCenters":[{"id":191,"text":"Colorado Water Science 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,{"id":70210282,"text":"70210282 - 2020 - Biofilms provide new insight into pesticide occurrence in streams and links to aquatic ecological communities","interactions":[],"lastModifiedDate":"2020-05-29T15:28:16.294568","indexId":"70210282","displayToPublicDate":"2020-04-20T10:19:05","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1565,"text":"Environmental Science & Technology","onlineIssn":"1520-5851","printIssn":"0013-936X","active":true,"publicationSubtype":{"id":10}},"title":"Biofilms provide new insight into pesticide occurrence in streams and links to aquatic ecological communities","docAbstract":"Streambed sediment is commonly analyzed to assess occurrence of hydrophobic pesticides and risks to aquatic communities. However, stream biofilms also have the potential to accumulate pesticides and may be consumed by aquatic organisms. To better characterize risks to aquatic life, the U.S. Geological Survey Regional Stream Quality Assessment measured 93 current-use and 3 legacy pesticides in bed sediment and biofilm from 54 small streams in California across a range of land-use settings. On average, 4 times as many current-use pesticides were detected in biofilm at a site (median of 2) as in sediment (median of 0.5). Of 31 current-use pesticides detected, 20 were detected more frequently in biofilm than sediment and 10 equally frequently. Pyrethroids as a class were the most potentially toxic to benthic invertebrates, and of the nine pyrethroids detected, seven occurred more frequently in biofilm than sediment. We constructive General Additive Models to investigate relations between pesticides and six metrics of benthic community structure. Pesticides in biofilm improved fit in four of the six models, and pesticides in sediment improved fit in two. The results indicate that sampling of stream biofilms can complement bed-sediment sampling by identifying more current-use pesticides present and better estimating ecological risks.","language":"English","publisher":"American Chemical Society","doi":"10.1021/acs.est.9b07430","usgsCitation":"Mahler, B., Schmidt, T., Nowell, L.H., Qi, S.L., Van Metre, P.C., Hladik, M.L., Carlisle, D.M., Munn, M., and May, J., 2020, Biofilms provide new insight into pesticide occurrence in streams and links to aquatic ecological communities: Environmental Science & Technology, v. 54, no. 9, p. 5509-5519, https://doi.org/10.1021/acs.est.9b07430.","productDescription":"11 p.","startPage":"5509","endPage":"5519","ipdsId":"IP-114380","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":437021,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9YYD8DI","text":"USGS data release","linkHelpText":"Concentrations of pesticides associated with streambed sediment and biofilm in California streams, 2017"},{"id":375146,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -119.520263671875,\n              34.34343606848294\n            ],\n            [\n              -118.5205078125,\n              34.813803317113155\n            ],\n            [\n              -120.684814453125,\n              37.21283151445594\n            ],\n            [\n              -121.56372070312499,\n              38.487994609214795\n            ],\n            [\n              -122.025146484375,\n              39.027718840211605\n            ],\n            [\n              -123.53027343749999,\n              38.75408327579141\n            ],\n            [\n              -122.64038085937499,\n              37.32648861334206\n            ],\n            [\n              -121.95922851562501,\n              36.29741818650811\n            ],\n            [\n              -120.69580078125001,\n              34.89494244739732\n            ],\n            [\n              -120.62988281249999,\n              34.50655662164561\n            ],\n            [\n              -119.520263671875,\n              34.34343606848294\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"54","issue":"9","noUsgsAuthors":false,"publicationDate":"2020-04-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Mahler, Barbara 0000-0002-9150-9552 bjmahler@usgs.gov","orcid":"https://orcid.org/0000-0002-9150-9552","contributorId":1249,"corporation":false,"usgs":true,"family":"Mahler","given":"Barbara","email":"bjmahler@usgs.gov","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - 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,{"id":70210970,"text":"70210970 - 2020 - Subduction megathrust heterogeneity characterized from 3D seismic data","interactions":[],"lastModifiedDate":"2020-07-08T15:21:30.577495","indexId":"70210970","displayToPublicDate":"2020-04-20T10:13:50","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2845,"text":"Nature Geoscience","active":true,"publicationSubtype":{"id":10}},"title":"Subduction megathrust heterogeneity characterized from 3D seismic data","docAbstract":"<p><span>Megathrust roughness and structural complexity are thought to be controls on earthquake slip at subduction zones because they result in heterogeneity in shear strength and resolved stress. However, because active megathrust faults are difficult to observe, the causes and scales of complexity are largely unknown. Here we measured the in situ properties of the megathrust of the Middle America subduction zone in a three-dimensional seismic reflection volume to determine how fault properties vary. We quantify spatial variability in the megathrust roughness, overburden and rock physical properties. Heterogeneity in the megathrust roughness exists at length scales of a few kilometres because the megathrust is dissected by active lower-plate normal faults, which offset the megathrust and renewed fault roughness. Spatial variations in the rock physical properties at the plate interface are characterized by correlation length scales of hundreds of metres. Frontal prism taper, historical seismicity and the variation in earthquake stress drop values local to the megathrust are all affected by the heterogeneity at these length scales. Both geometric and rheological complexities may therefore control the mechanical behaviour of the subduction plate interface, which includes earthquake rupture characteristics.</span></p>","language":"English","publisher":"Nature","doi":"10.1038/s41561-020-0562-9","usgsCitation":"Kirkpatrick, J.D., Edwards, J.H., Verdecchia, A., Kluesner, J.W., Harrington, R.M., and Silver, E., 2020, Subduction megathrust heterogeneity characterized from 3D seismic data: Nature Geoscience, v. 13, p. 369-374, https://doi.org/10.1038/s41561-020-0562-9.","productDescription":"6 p.","startPage":"369","endPage":"374","ipdsId":"IP-106884","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":467292,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://escholarship.mcgill.ca/concern/articles/pc289q07k","text":"External Repository"},{"id":376202,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Costa Rica","otherGeospatial":"Central America megathrust, Pacific Ocean","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -86.68212890625,\n              8.222363866437243\n            ],\n            [\n              -83.77349853515625,\n              8.222363866437243\n            ],\n            [\n              -83.77349853515625,\n              9.584500864717143\n            ],\n            [\n              -86.68212890625,\n              9.584500864717143\n            ],\n            [\n              -86.68212890625,\n              8.222363866437243\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"13","noUsgsAuthors":false,"publicationDate":"2020-04-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Kirkpatrick, James D.","contributorId":202603,"corporation":false,"usgs":false,"family":"Kirkpatrick","given":"James","email":"","middleInitial":"D.","affiliations":[{"id":6646,"text":"McGill University","active":true,"usgs":false}],"preferred":false,"id":792312,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Edwards, Joel H.","contributorId":202599,"corporation":false,"usgs":false,"family":"Edwards","given":"Joel","email":"","middleInitial":"H.","affiliations":[{"id":27155,"text":"University of California Santa Cruz","active":true,"usgs":false}],"preferred":false,"id":792313,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Verdecchia, Alessandro","contributorId":228863,"corporation":false,"usgs":false,"family":"Verdecchia","given":"Alessandro","email":"","affiliations":[{"id":41521,"text":"Ruhr-Universität Bochum","active":true,"usgs":false}],"preferred":false,"id":792314,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kluesner, Jared W. 0000-0003-1701-8832 jkluesner@usgs.gov","orcid":"https://orcid.org/0000-0003-1701-8832","contributorId":201261,"corporation":false,"usgs":true,"family":"Kluesner","given":"Jared","email":"jkluesner@usgs.gov","middleInitial":"W.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":792315,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Harrington, Rebecca M.","contributorId":146633,"corporation":false,"usgs":false,"family":"Harrington","given":"Rebecca","email":"","middleInitial":"M.","affiliations":[{"id":16736,"text":"Dept. of Earth and Planetary Sci,.McGill Univ., Montreal, Quebec","active":true,"usgs":false}],"preferred":false,"id":792316,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Silver, Eli","contributorId":173114,"corporation":false,"usgs":false,"family":"Silver","given":"Eli","affiliations":[{"id":27155,"text":"University of California Santa Cruz","active":true,"usgs":false}],"preferred":false,"id":792317,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70210161,"text":"70210161 - 2020 - The Landsat Burned Area algorithm and products for the conterminous United States","interactions":[],"lastModifiedDate":"2022-04-14T19:23:11.991912","indexId":"70210161","displayToPublicDate":"2020-04-20T10:12:38","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3254,"text":"Remote Sensing of Environment","printIssn":"0034-4257","active":true,"publicationSubtype":{"id":10}},"title":"The Landsat Burned Area algorithm and products for the conterminous United States","docAbstract":"Complete and accurate burned area map data are needed to document spatial and temporal patterns of fires, to quantify their drivers, and to assess the impacts on human and natural systems. In this study, we developed the Landsat Burned Area (BA) algorithm, an update from the Landsat Burned Area Essential Climate Variable (BAECV) algorithm. Here, we present the BA algorithm and products, changes relative to the BAECV algorithm and products, and updated validation metrics. We also present spatial and temporal patterns of burned area across the conterminous U.S., how burned area varies in relation to the number of operational Landsat sensors, and a comparison with other burned area datasets, including the BAECV, Monitoring Trends in Burn Severity (MTBS), GeoMAC, and Moderate Resolution Imaging Spectroradiometer (MODIS) MCD64A1.006 data. The BA algorithm identifies burned areas in analysis ready data (ARD) time-series of Landsat imagery from 1984 through 2018 using machine learning, thresholding, and image segmentation. Validation with reference data from high-resolution commercial satellite imagery resulted in omission and commission error rates averaging 19% and 41%, respectively. In comparison, validation with Landsat reference data had omission and commission error rates averaging 40% and 28%, respectively when burned areas in cultivated crops and pasture/hay land-cover types were excluded. Both validation tests documented lower commission error rates relative to the BAECV products. The amount of burned area detected varies not only in response to climate but also with the number of operational sensors and scenes collected. The combined amount of burned area detected by multiple sensors was larger than from any individual sensor, but there was no significant difference between individual sensors. Therefore, we used BA products from individual sensors to assess trends over time and all available sensors to compare with other existing BA products. From 1984 through 2018, annual burned area averaged 30,000 km2, ranged between 14,000 km2 in 1991 and 46,500 km2 in 2012, and increased over time at a rate of 356 km2/year. Compared to existing burned area products, the new Landsat BA products identified 29% more burned area than the BAECV products (1984–2015), 183% more than the MTBS/GeoMAC products (1984–2018), and 56% more than the MCD64A1.006 products (2003–2018). The products had similar patterns of year-to-year variability; the R2 values of linear regressions between annual burned area were >0.70 with the BAECV products and the MTBS/GeoMAC products, but somewhat lower for the MCD64A1.006 product (R2 = 0.66). The BA products are routinely produced as new Landsat data are collected and provide a unique data source to monitor and assess the spatial and temporal patterns and the impacts of fire.","language":"English","publisher":"Elsevier","doi":"10.1016/j.rse.2020.111801","usgsCitation":"Hawbaker, T., Vanderhoof, M.K., Schmidt, G.L., Beal, Y.G., Picotte, J.J., Takacs, J., Falgout, J.T., and Dwyer, J.L., 2020, The Landsat Burned Area algorithm and products for the conterminous United States: Remote Sensing of Environment, v. 244, 111801, 24 p., https://doi.org/10.1016/j.rse.2020.111801.","productDescription":"111801, 24 p.","ipdsId":"IP-111890","costCenters":[{"id":208,"text":"Core Science Analytics and Synthesis","active":true,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":457018,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.rse.2020.111801","text":"Publisher Index Page"},{"id":437022,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9F26LY6","text":"USGS data release","linkHelpText":"The Landsat Collection 2 Burned Area Products for the conterminous United States (ver. 2.0, April 2024)"},{"id":374927,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"geometry\": {\n        \"type\": \"MultiPolygon\",\n        \"coordinates\": [\n          [\n            [\n              [\n                -94.81758,\n                49.38905\n              ],\n              [\n                -94.64,\n                48.84\n              ],\n   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,{"id":70214062,"text":"70214062 - 2020 - Localized outbreaks of coral disease on Arabian reefs are linked to extreme temperatures and environmental stressors","interactions":[],"lastModifiedDate":"2020-09-22T14:52:08.334936","indexId":"70214062","displayToPublicDate":"2020-04-20T09:44:45","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1338,"text":"Coral Reefs","active":true,"publicationSubtype":{"id":10}},"title":"Localized outbreaks of coral disease on Arabian reefs are linked to extreme temperatures and environmental stressors","docAbstract":"<p><span>The Arabian Peninsula borders the hottest reefs in the world, and corals living in these extreme environments can provide insight into the effects of warming on coral health and disease. Here, we examined coral reef health at 17 sites across three regions along the northeastern Arabian Peninsula (Persian Gulf, Strait of Hormuz and Oman Sea) representing a gradient of environmental conditions. The Persian Gulf has extreme seasonal fluctuations in temperature and chronic hypersalinity, whereas the other two regions experience more moderate conditions. Field surveys identified 13 coral diseases including tissue loss diseases of unknown etiology (white syndromes) in&nbsp;</span><i>Porites, Platygyra</i><span>,&nbsp;</span><i>Dipsastraea</i><span>,&nbsp;</span><i>Cyphastrea, Acropora</i><span>&nbsp;and&nbsp;</span><i>Goniopora</i><span>; growth anomalies in&nbsp;</span><i>Porites, Platygyra</i><span>&nbsp;and&nbsp;</span><i>Dipsastraea</i><span>; black band disease in&nbsp;</span><i>Platygyra</i><span>,&nbsp;</span><i>Dipsastraea</i><span>,&nbsp;</span><i>Acropora, Echinopora</i><span>&nbsp;and&nbsp;</span><i>Pavona</i><span>; bleached patches in&nbsp;</span><i>Porites</i><span>&nbsp;and&nbsp;</span><i>Goniopora</i><span>&nbsp;and a disease unique to this region, yellow-banded tissue loss in&nbsp;</span><i>Porites</i><span>. The most widespread diseases were&nbsp;</span><i>Platygyra</i><span>&nbsp;growth anomalies (52.9% of all surveys),&nbsp;</span><i>Acropora</i><span>&nbsp;white syndrome (47.1%) and&nbsp;</span><i>Porites</i><span>&nbsp;bleached patches (35.3%). We found a number of diseases not yet reported in this region and found differential disease susceptibility among coral taxa. Disease prevalence was higher on reefs within the Persian Gulf (avg. 2.05%) as compared to reefs within the Strait of Hormuz (0.46%) or Oman Sea (0.25%). A high number of localized disease outbreaks (8 of 17 sites) were found, especially within the Persian Gulf (5 of 8 sites). Across all regions, the majority of variation in disease prevalence (82.2%) was associated with the extreme temperature range experienced by these corals combined with measures of organic pollution and proximity to shore. Thermal stress is known to drive a number of coral diseases, and thus, this region provides a platform to study disease at the edge of corals’ thermal range.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s00338-020-01928-4","usgsCitation":"Aeby, G.S., Howells, E., Work, T.M., Abrego, D., Williams, G.J., Wedding, L.M., Caldwell, J.M., Moritsch, M.M., and Burt, J., 2020, Localized outbreaks of coral disease on Arabian reefs are linked to extreme temperatures and environmental stressors: Coral Reefs, v. 39, p. 829-846, https://doi.org/10.1007/s00338-020-01928-4.","productDescription":"18 p.","startPage":"829","endPage":"846","ipdsId":"IP-117756","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":457021,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s00338-020-01928-4","text":"Publisher Index Page"},{"id":378662,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Oman, United Arab Emirates","otherGeospatial":"Gulf of Oman, Persian Gulf, Strait of Hormuz","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              51.8115234375,\n              23.765236889758672\n            ],\n            [\n              56.953125,\n              23.765236889758672\n            ],\n            [\n              56.953125,\n              26.667095801104814\n            ],\n            [\n              51.8115234375,\n              26.667095801104814\n            ],\n            [\n              51.8115234375,\n              23.765236889758672\n            ]\n          ]\n        ]\n      }\n    }\n  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