{"pageNumber":"652","pageRowStart":"16275","pageSize":"25","recordCount":165270,"records":[{"id":70212697,"text":"70212697 - 2019 - Analog experiments of lava flow emplacement","interactions":[],"lastModifiedDate":"2020-08-26T13:21:50.661146","indexId":"70212697","displayToPublicDate":"2019-12-31T07:12:47","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":793,"text":"Annals of Geophysics","active":true,"publicationSubtype":{"id":10}},"title":"Analog experiments of lava flow emplacement","docAbstract":"<p>Laboratory experiments that simulate lava flows have been in use by volcanologists for many years. The behavior of flows in the lab, where “eruption” parameters, material properties, and environmental settings are tightly controlled, provides insight into the influence of various factors on flow evolution. A second benefit of laboratory lava flows is to provide a set of observations with which numerical models of flow emplacement can be tested. Models of lava flow emplacement vary in mathematical approach, physical assumptions, and computational cost. Nonetheless, all models require thorough testing and evaluation, and laboratory experiments produce an excellent test for models.</p><p>This paper provides a primer on modern analog laboratory lava flow experiments. It reviews scaling con- siderations and provides quantitative information meant to guide future experimentalists in designing their experiments to be relevant to natural processes. Traditional and novel laboratory techniques are described, including a discussion of current limitations. New insights from recent experiments highlight the impact of topographic conditions and highlight the importance of considering bed roughness, major obstacles, and slope breaks. The influence of episodic or non-uniform effusion rate is demonstrated through recent experi- mental works. Lastly, the paper discusses several open questions about lava flow emplacement and the ways in which future improvements in experimental methods, such as the ability to utilize three-phase suspensions and materials with complex rheologies and to image the interior of flows could help answer these.</p>","language":"English","publisher":"National Institute of Geophysics and Volcanology (INGV)","doi":"10.4401/ag-7843","usgsCitation":"Lev, E., Rumpf, M.E., and Dietterich, H., 2019, Analog experiments of lava flow emplacement: Annals of Geophysics, v. 62, no. 2, VO225, 21 p., https://doi.org/10.4401/ag-7843.","productDescription":"VO225, 21 p.","ipdsId":"IP-103534","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":458876,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.4401/ag-7843","text":"Publisher Index Page"},{"id":377875,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"62","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Lev, Einat 0000-0002-8174-0558","orcid":"https://orcid.org/0000-0002-8174-0558","contributorId":194355,"corporation":false,"usgs":false,"family":"Lev","given":"Einat","email":"","affiliations":[{"id":27369,"text":"Lamont-Doherty Earth Observatory at Columbia University","active":true,"usgs":false}],"preferred":false,"id":797292,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rumpf, M. Elise 0000-0001-7906-2623","orcid":"https://orcid.org/0000-0001-7906-2623","contributorId":217992,"corporation":false,"usgs":true,"family":"Rumpf","given":"M.","email":"","middleInitial":"Elise","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":797294,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dietterich, Hannah R. 0000-0001-7898-4343","orcid":"https://orcid.org/0000-0001-7898-4343","contributorId":212771,"corporation":false,"usgs":true,"family":"Dietterich","given":"Hannah R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":797293,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70208836,"text":"70208836 - 2019 - Gopherus agassizii (Cooper 1861) – Agassiz’s Desert Tortoise, Mojave Desert Tortoise","interactions":[],"lastModifiedDate":"2021-12-10T15:22:19.1894","indexId":"70208836","displayToPublicDate":"2019-12-31T06:51:39","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5938,"text":"Chelonian Research Monographs","printIssn":"1088-7105","active":true,"publicationSubtype":{"id":10}},"displayTitle":"<i>Gopherus agassizii</i> (Cooper 1861) – Agassiz’s Desert Tortoise, Mojave Desert Tortoise","title":"Gopherus agassizii (Cooper 1861) – Agassiz’s Desert Tortoise, Mojave Desert Tortoise","docAbstract":"<div>The Mojave Desert Tortoise,<span>&nbsp;</span><i>Gopherus agassizii</i><span>&nbsp;</span>(Family Testudinidae), is a large terrestrial species that can reach &gt;370 mm in straight midline carapace length (CL) but most individuals are smaller. Both sexes reach adulthood at 12 to 21 years and ca. 180 mm CL. The species is sexually dimorphic, with males typically larger than females; sexual characteristics of males become more obvious with increasing size and age. Females lay from 1 to 10 eggs per clutch and from 0 to 3 clutches annually, with eggs hatching after 67 to 104 days. Populations of<span>&nbsp;</span><i>G. agassizii</i><span>&nbsp;</span>have declined rapidly over the last several decades. Habitat throughout the geographic range has experienced major losses, degradation, and fragmentation as a result of urban and agricultural development, livestock grazing, military activities, transportation and utility corridors, high levels of visitor use, vehicle-oriented recreation, and energy development. Disturbed habitats were vulnerable to invading non-native grasses and forbs, creating an unnatural and destructive grass-fire cycle. When consumed by tortoises as their only diet, non-native (and native) grasses are harmful because of limited nutrients. Additionally, subsidized predators (Common Ravens, Coyotes, and dogs), infectious diseases, drought, and vandalism, add to the catastrophic effects of habitat loss and degradation. Tortoise populations have declined rapidly in density, and most populations are below viability, with fewer than 3.9 adults/km2. These declines occurred despite protections afforded by federal and state laws and regulations, ca. 26,000 km2 of federally designated critical habitat units, two Recovery Plans, and efforts to reduce the negative impacts of human activities. As noted by Allison and McLuckie (2018), the negative population trends in most of the critical habitat units suggest that under current conditions<span>&nbsp;</span><i>G. agassizii</i><span>&nbsp;</span>is on the path to extinction.</div><div><strong>Distribution.</strong><span>&nbsp;</span>– USA. Distributed in parts of the southern Great Basin, Mojave, and western Sonoran deserts in southeastern California, southern Nevada, northwestern Arizona, and southwestern Utah, north and west of the Grand Canyon/Colorado River complex, with the exception of a small population east of the Colorado River.</div><div><strong>Synonymy.</strong><span>&nbsp;</span>–<span>&nbsp;</span><i>Xerobates agassizii</i><span>&nbsp;</span>Cooper 1861,<span>&nbsp;</span><i>Testudo agassizii, Gopherus agassizii, Gopherus polyphemus agassizii, Scaptochelys agassizii, Xerobates lepidocephalus</i><span>&nbsp;</span>Ottley and Velázques Solis 1989.</div><div><strong>Subspecies</strong>. – None currently recognized.</div><div><strong>Status.</strong><span>&nbsp;</span>– IUCN 2019 Red List:<span>&nbsp;</span><a href=\"https://www.iucnredlist.org/species/9400/12983037\" data-mce-href=\"https://www.iucnredlist.org/species/9400/12983037\"><span>Vulnerable (VU A1acde+2cde; assessed 1996)</span></a>; TFTSG Provisional Red List: Critically Endangered (CR; assessed 2011, 2018); CITES: Appendix II (Testudinidae spp.); US ESA: Threatened.</div>","language":"English","publisher":"Chelonian Research Foundation and Turtle Conservancy","doi":"10.3854/crm.5.109.agassizii.v1.2019","usgsCitation":"Berry, K.H., and Murphy, R.W., 2019, Gopherus agassizii (Cooper 1861) – Agassiz’s Desert Tortoise, Mojave Desert Tortoise: Chelonian Research Monographs, v. 5, no. 13, p. 1-43, https://doi.org/10.3854/crm.5.109.agassizii.v1.2019.","productDescription":"44 p.","startPage":"1","endPage":"43","ipdsId":"IP-111073","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":458880,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3854/crm.5.109.agassizii.v1.2019","text":"Publisher Index Page"},{"id":372942,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, California, Nevada, Utah","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -116.630859375,\n              36.491973470593685\n            ],\n            [\n              -117.7734375,\n              35.496456056584165\n            ],\n            [\n              -116.630859375,\n              33.87041555094183\n            ],\n            [\n              -114.9169921875,\n              32.69486597787505\n            ],\n            [\n              -114.169921875,\n              33.17434155100208\n            ],\n            [\n              -114.0380859375,\n              34.34343606848294\n            ],\n            [\n              -114.169921875,\n              35.460669951495305\n            ],\n            [\n              -113.64257812499999,\n              37.33522435930639\n            ],\n            [\n              -112.412109375,\n              37.68382032669382\n            ],\n            [\n              -112.4560546875,\n              38.272688535980976\n            ],\n            [\n              -114.521484375,\n              37.579412513438385\n            ],\n            [\n              -116.103515625,\n              36.84446074079564\n            ],\n            [\n              -116.630859375,\n              36.491973470593685\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"5","issue":"13","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Berry, Kristin H. 0000-0003-1591-8394 kristin_berry@usgs.gov","orcid":"https://orcid.org/0000-0003-1591-8394","contributorId":437,"corporation":false,"usgs":true,"family":"Berry","given":"Kristin","email":"kristin_berry@usgs.gov","middleInitial":"H.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":783568,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Murphy, Robert W.","contributorId":147498,"corporation":false,"usgs":false,"family":"Murphy","given":"Robert","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":783569,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70208580,"text":"70208580 - 2019 - Genetically-informed seed transfer zones for Pleuraphis jamesii, Sphaeralcea parvifolia, and Sporobolus cryptandrus across the Colorado Plateau and adjacent regions","interactions":[],"lastModifiedDate":"2020-02-20T06:51:01","indexId":"70208580","displayToPublicDate":"2019-12-31T06:48:01","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Genetically-informed seed transfer zones for Pleuraphis jamesii, Sphaeralcea parvifolia, and Sporobolus cryptandrus across the Colorado Plateau and adjacent regions","docAbstract":"(Massatti) Introduction: The majority of native plant materials (NPMs) utilized for restoration purposes are developed for widely distributed species that provide a variety of ecosystem services (Wood et al. 2015; Butterfield et al. 2017). Disturbed ecosystems benefit from the use of appropriate NPMs, which are those that display ecological fitness at the restoration site, are compatible with conspecifics and other members of the plant community, and that do not demonstrate invasive tendencies (Jones 2013). Furthermore, the use of appropriate NPMs can help address specific environmental challenges, rejuvenate ecosystem function, and improve the delivery of ecosystem services (Hughes 2008). While many NPMs have been developed for restoration (e.g., Aubry et al. 2005), there is interest in broadening the diversity of species available and the geographic representation of sources to provide appropriate choices in relation to the characteristics of any restoration site. In addition, researchers are providing guidance to managers and practitioners regarding how best to transfer NPMs across the landscape. For example, guidance on seed transfer has been derived from genecological studies, which utilize common gardens to correlate phenotypic variation to environmental gradients (summarized in Kilkenny 2015), molecular studies, which identify putative adaptive genetic loci and infer environmental drivers of variation (Shryock et al. 2017), and climate modeling studies, which can provide guidance when species-specific data are unavailable (Bower et al. 2014; Doherty et al. 2017). All of these approaches intend to improve the long-term viability of NPMs at restoration sites, thereby improving outcomes and stretching limiting restoration resources (e.g., time and money).","language":"English","publisher":"Bureau of Land Management","usgsCitation":"Massatti, R., 2019, Genetically-informed seed transfer zones for Pleuraphis jamesii, Sphaeralcea parvifolia, and Sporobolus cryptandrus across the Colorado Plateau and adjacent regions, 11 p.","productDescription":"11 p.","ipdsId":"IP-113144","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":372440,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":372412,"type":{"id":15,"text":"Index Page"},"url":"https://www.blm.gov/sites/blm.gov/files/GWRC_STZ_report1.pdf"}],"country":"United States","otherGeospatial":"Colorado Plateau ","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -119.42138671875,\n              39.57182223734374\n            ],\n            [\n              -118.23486328125,\n              36.65079252503471\n            ],\n            [\n              -111.7529296875,\n              33.76088200086917\n            ],\n            [\n              -107.1826171875,\n              33.137551192346145\n            ],\n            [\n              -104.0185546875,\n              33.284619968887675\n            ],\n            [\n              -104.7216796875,\n              39.027718840211605\n            ],\n            [\n              -107.70996093749999,\n              40.111688665595956\n            ],\n            [\n              -111.4013671875,\n              41.77131167976407\n            ],\n            [\n              -114.5654296875,\n              42.52069952914966\n            ],\n            [\n              -117.2900390625,\n              42.06560675405716\n            ],\n            [\n              -118.87207031250001,\n              40.84706035607122\n            ],\n            [\n              -119.42138671875,\n              39.57182223734374\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Massatti, Robert 0000-0001-5854-5597","orcid":"https://orcid.org/0000-0001-5854-5597","contributorId":207294,"corporation":false,"usgs":true,"family":"Massatti","given":"Robert","email":"","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":782587,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70208336,"text":"70208336 - 2019 - Quantifying changes to infaunal communities associated with several deep-sea coral habitats in the Gulf of Mexico and their potential recovery from the DWH oil spill","interactions":[],"lastModifiedDate":"2020-02-05T06:50:04","indexId":"70208336","displayToPublicDate":"2019-12-31T06:46:56","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Quantifying changes to infaunal communities associated with several deep-sea coral habitats in the Gulf of Mexico and their potential recovery from the DWH oil spill","docAbstract":"Extensive information is available about infaunal soft-sediment communities in the Gulf of Mexico (Gulf) (Pequegnat et al. 1990, Rowe and Kennicutt II 2009, Wei et al. 2010), particularly from the large-scale sampling effort of the Deep Gulf of Mexico Benthos (DGOMB) project in the early 2000s (Rowe and Kennicutt II 2009). Infaunal soft-sediment communities in the northern Gulf differ by geographic location and depth (Rowe and Kennicutt II 2009, Wei et al. 2010). Density decreases with depth, while taxa diversity exhibits a mid-depth (1,100-1,300 m) maximum (Rowe and Kennicutt II 2009). Community composition is influenced by both geographic location and depth, with zones (as defined by Wei et al. 2010) encompassing specific depth ranges, ranging from 635 to 3,314 m, and separated into east and west components. These zones were correlated to detrital particulate organic carbon (POC) export flux, primarily from the Mississippi River (Wei et al. 2010), where POC flux decreases with depth (Biggs et al. 2008). The flux of POC has also been found to be higher in the northeast Gulf than the northwest (Biggs et al. 2008), and consequently, biomass of infaunal communities is positively correlated with sedimentorganic carbon content (Morse and Beazley 2008).\n\nMost of the deep Gulf is composed of soft-sediment environments, but the relative flat seafloor is\npunctuated in areas with other heterogeneous habitats, including chemosynthetic environments and deepsea coral habitats. Deep-sea corals create a complex three-dimensional structure that enhances local biodiversity, supporting diverse and abundant fish and invertebrate communities (Mortensen et al. 1995, Costello et al. 2005, Henry and Roberts 2007, Ross and Quattrini 2007, Buhl-Mortensen et al. 2010). In recent years, knowledge of the sphere of influence of deep-sea corals has expanded, with evidence that coral habitats also influence surrounding sediments (Mienis et al. 2012, Demopoulos et al. 2014, Fisher et al. 2014, Demopoulos et al. 2016, Bourque and Demopoulos 2018). Deep-sea corals are capable of altering their associated biotic and abiotic environment, thus serving as ecosystem engineers (e.g., Jones et al. 1994). The depositional environment and associated hydrodynamic regime around coral habitats differ from the extensive expanses of soft-sediments that dominate the sea floor (e.g., Mienis et al. 2009a. 2009a, Mienis et al. 2009b, Mienis et al. 2012), with the three-dimensional structure of the coral causing turbulent flows that enhance sediment accumulation adjacent to coral structures. In the northern Gulf, deep-sea corals generally occur on mounds of authigenic carbonate (Schroeder 2002) where elevation above the benthic boundary layer into higher velocity laminar flows allows for increased availability of food resources (Buhl-Mortensen and Mortensen 2005). The different hydrodynamics around corals likely affects the sediment geochemistry and in turn infaunal community structure and function (Demopoulos et al. 2014).\n\nEcosystem-based research on Gulf infaunal communities has primarily focused on soft-sediment\nenvironments. Initial research on deep-sea coral-associated infaunal communities focused on Lophelia pertusa (e.g., Demopoulos et al. 2014), and more recent studies focused on octocorals (Fisher et al. 2014, Demopoulos et al. 2016, Bourque and Demopoulos 2018) and comparisons among coral habitat types (Bourque and Demopoulos 2018). Coral-adjacent sediment communities are distinctly different from nearby background soft-sediment (Demopoulos et al. 2014, Bourque and Demopoulos 2018), with a sphere of influence estimated to be between 14 and 100 m (Demopoulos et al. 2014, Bourque and Demopoulos 2018). The coral type (e.g., L. pertusa, Madrepora oculata, octocorals) also influences sediment communities, with L. pertusa habitats distinct from both M. oculata and octocoral habitats (Bourque and Demopoulos 2018). Differences among coral communities are influenced by depth,","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"OCS Study BOEM 2019-033","largerWorkSubtype":{"id":4,"text":"Other Government Series"},"language":"English","publisher":"Bureau of Ocean Energy Management","usgsCitation":"Bourque, J.R., and Demopoulos, A.W., 2019, Quantifying changes to infaunal communities associated with several deep-sea coral habitats in the Gulf of Mexico and their potential recovery from the DWH oil spill, iv, 35 p.","productDescription":"iv, 35 p.","ipdsId":"IP-099020","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":372049,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":372020,"type":{"id":15,"text":"Index Page"},"url":"https://espis.boem.gov/final%20reports/BOEM_2019-033.pdf"}],"country":"United States, Mexico","otherGeospatial":"Gulf of Mexico","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -80.595703125,\n              25.48295117535531\n            ],\n            [\n              -82.529296875,\n              29.916852233070173\n            ],\n            [\n              -84.90234375,\n              30.826780904779774\n            ],\n            [\n              -89.47265625,\n              31.052933985705163\n            ],\n            [\n              -93.33984375,\n              30.44867367928756\n            ],\n            [\n              -97.470703125,\n              28.92163128242129\n            ],\n            [\n              -99.052734375,\n              25.562265014427492\n            ],\n            [\n              -97.55859375,\n              21.453068633086783\n            ],\n            [\n              -96.240234375,\n              18.646245142670608\n            ],\n            [\n              -91.58203125,\n              17.644022027872726\n            ],\n            [\n              -89.82421875,\n              19.642587534013032\n            ],\n            [\n              -86.220703125,\n              22.268764039073968\n            ],\n            [\n              -80.595703125,\n              25.48295117535531\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Bourque, Jill R. 0000-0003-3809-2601 jbourque@usgs.gov","orcid":"https://orcid.org/0000-0003-3809-2601","contributorId":5452,"corporation":false,"usgs":true,"family":"Bourque","given":"Jill","email":"jbourque@usgs.gov","middleInitial":"R.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":781504,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Demopoulos, Amanda W.J. 0000-0003-2096-4694 ademopoulos@usgs.gov","orcid":"https://orcid.org/0000-0003-2096-4694","contributorId":145681,"corporation":false,"usgs":true,"family":"Demopoulos","given":"Amanda","email":"ademopoulos@usgs.gov","middleInitial":"W.J.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":781505,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70208860,"text":"70208860 - 2019 - Cultivating future environmental stewards: A case study at John D. MacArthur Beach State Park","interactions":[],"lastModifiedDate":"2020-03-04T06:36:22","indexId":"70208860","displayToPublicDate":"2019-12-31T06:36:10","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1672,"text":"Florida Scientist","active":true,"publicationSubtype":{"id":10}},"title":"Cultivating future environmental stewards: A case study at John D. MacArthur Beach State Park","docAbstract":"Our study supports previous research suggesting that participation in citizen-science programs can significantly enhance student learning and attitudes about science, while simultaneously promoting environmental stewardship. Providing students with the opportunity to collect scientific data through citizen-science programs can increase their understanding of local ecosystems, enhance their observation skills, and can improve their understanding of the scientific process.","language":"English","publisher":"Florida Academy of Sciences","usgsCitation":"Frehm, V.L., Gravinese, P.M., and Toth, L., 2019, Cultivating future environmental stewards: A case study at John D. MacArthur Beach State Park: Florida Scientist, v. 82, no. 4, p. 112-121.","productDescription":"10 p.","startPage":"112","endPage":"121","ipdsId":"IP-107939","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":372881,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"John D. MacArthur Beach State Park","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -80.05325317382812,\n              26.837091180589052\n            ],\n            [\n              -80.04947662353516,\n              26.823304827976315\n            ],\n            [\n              -80.05136489868164,\n              26.8179430155512\n            ],\n            [\n              -80.04570007324219,\n              26.807831479104824\n            ],\n            [\n              -80.03780364990234,\n              26.81334697442843\n            ],\n            [\n              -80.03437042236328,\n              26.814725806332714\n            ],\n            [\n              -80.03952026367188,\n              26.837244352859237\n            ],\n            [\n              -80.05325317382812,\n              26.837091180589052\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"82","issue":"4","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Frehm, Veronica L.","contributorId":222982,"corporation":false,"usgs":false,"family":"Frehm","given":"Veronica","email":"","middleInitial":"L.","affiliations":[{"id":40632,"text":"John D. MacArthur Beach State Park","active":true,"usgs":false}],"preferred":false,"id":783713,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gravinese, Philip M.","contributorId":176801,"corporation":false,"usgs":false,"family":"Gravinese","given":"Philip","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":783714,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Toth, Lauren T. 0000-0002-2568-802X ltoth@usgs.gov","orcid":"https://orcid.org/0000-0002-2568-802X","contributorId":181748,"corporation":false,"usgs":true,"family":"Toth","given":"Lauren","email":"ltoth@usgs.gov","middleInitial":"T.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":783712,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
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href=\"https://www.usgs.gov/centers/asc/connect\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov/centers/asc/connect\">Director</a>,<br><a href=\"https://www.usgs.gov/centers/asc/\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov/centers/asc/\">Alaska Science Center</a><br><a href=\"https://www.usgs.gov/\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov/\">U.S. Geological Survey</a><br>4210 University Drive<br>Anchorage, Alaska 99508</p>","tableOfContents":"<ul><li>Director’s Message</li><li>Alaska Organizational Overview</li><li>Structure of Report</li><li>Icon Legend</li><li>Project Descriptions</li><li>Acronyms</li><li>Active Research Partners</li></ul><p><br></p>","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"publishedDate":"2019-12-30","noUsgsAuthors":false,"publicationDate":"2019-12-30","publicationStatus":"PW","contributors":{"editors":[{"text":"Williams, Dee 0000-0003-0400-479X","orcid":"https://orcid.org/0000-0003-0400-479X","contributorId":221172,"corporation":false,"usgs":true,"family":"Williams","given":"Dee","email":"","affiliations":[{"id":113,"text":"Alaska Regional Director's Office","active":true,"usgs":true}],"preferred":true,"id":778662,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Powers, Elizabeth 0000-0002-4688-1195","orcid":"https://orcid.org/0000-0002-4688-1195","contributorId":221171,"corporation":false,"usgs":true,"family":"Powers","given":"Elizabeth","email":"","affiliations":[{"id":113,"text":"Alaska Regional Director's Office","active":true,"usgs":true}],"preferred":true,"id":778663,"contributorType":{"id":2,"text":"Editors"},"rank":2}]}}
,{"id":70207363,"text":"ofr20191146 - 2019 - National assessment of shoreline change — Historical shoreline change along the north coast of Alaska, Icy Cape to Cape Prince of Wales","interactions":[],"lastModifiedDate":"2022-04-21T20:19:46.880847","indexId":"ofr20191146","displayToPublicDate":"2019-12-30T15:54:44","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2019-1146","displayTitle":"National Assessment of Shoreline Change — Historical Shoreline Change Along the North Coast of Alaska, Icy Cape to Cape Prince of Wales","title":"National assessment of shoreline change — Historical shoreline change along the north coast of Alaska, Icy Cape to Cape Prince of Wales","docAbstract":"<p>Beach erosion is a persistent problem along most open-ocean shores of the United States. Along the Arctic coast of Alaska, coastal erosion is widespread and threatens communities, defense and energy-related infrastructure, and coastal habitat. As coastal populations continue to expand and infrastructure and habitat are increasingly threatened by erosion, there is increased demand for accurate information regarding past and present trends and rates of shoreline movement.</p><p>Shoreline change was evaluated by comparing three to four historical shoreline positions derived from 1950s-era topographic surveys and black and white aerial photography, 1980s-era color-infrared Alaska High-Altitude Aerial Photography, 2003 natural color aerial photography, and 2010s-era natural color aerial photography. Long-term (1950s–2010s) and short-term (1980s–2010s) shoreline change rates were calculated using linear-regression and end-point methods, respectively, at transects spaced approximately every 50 meters along both the mainland and barrier island coasts.</p><p>Shoreline change rates calculated on more than 24,000 individual transects indicate that between 1948 and 2016 the northern coast of Alaska between Icy Cape and Cape Prince of Wales was slightly erosional, with 68 percent of the total transects showing shoreline retreat over the long term and 63 percent over the short term. However, only 9 percent of the total transects showed shoreline retreat greater than 1 meter per year (m/yr) over the long and short term, respectively. Mean rates of shoreline change of −0.2±0.1 and −0.2±0.3 m/yr, were calculated for the long and short term, respectively. Many rates measured were near the limit of our shoreline change uncertainty estimates. Erosion and accretion rates on individual transects ranged from −8.3 to +9.6 m/yr over the long term and −16.0 to +20.0 m/yr over the short-term analysis periods. The highest rates of erosion and accretion were associated with the formation and migration of inlets along barrier island coasts. The highest erosional rates of change were measured in the southern part of the study area between Sullivan Lake and Cape Prince of Wales. The highest accretional rates of change were measured in the northern part of the study area on the open-ocean coast of barrier islands fronting Kasegaluk Lagoon.</p><p>Open-ocean exposed shorelines compose 85 percent of all transects and 70 percent were erosional over the long term. Sheltered mainland-lagoon shorelines compose 15 percent of all transects in the study area and 58 percent were erosional over the long term. Although mean shoreline change rates were quite low along all coasts, exposed shorelines retreated at twice the rate (−0.2±0.1 m/yr) of sheltered shorelines (−0.1±0.1 m/yr). Barrier shoreline transects (includes barrier islands, spits, and beaches) compose 49 percent of the total transects and 56 percent of all exposed shoreline transects. Mean shoreline change rates on exposed barrier shorelines were only slightly greater than exposed mainland shorelines (−0.3±0.1 and −0.2±0.1 m/yr, respectively). Mean shoreline change rates on sheltered barrier shorelines were similar to sheltered mainland shorelines (−0.1±0.3 m/yr).</p><p>In contrast to the majority of the Nation’s shorelines, for all but three months of the year (July–September), the north coast of Alaska has historically been protected by landfast sea ice from processes such as waves, winds, and currents that typically drive coastal change on beaches in more temperate regions of the world. Projected and observed increases in periods of sea-ice-free conditions, as sea ice melts earlier and forms later in the year, particularly in the autumn, when large storms are more common in the Arctic, suggest that Arctic coasts will be more vulnerable to storm surge and wave energy, potentially resulting in accelerated shoreline erosion and terrestrial habitat loss in the future. Increases in air and sea water temperatures may also increase erosion of the ice-rich, coastal permafrost bluffs present along much of Alaska’s Arctic coast. More frequent shoreline change data collection and analysis in this rapidly changing environment should be considered in order to evaluate shoreline change trends in the future.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191146","usgsCitation":"Gibbs, A.E., Snyder, A.G., and Richmond, B.M., 2019, National assessment of shoreline change — Historical shoreline change along the north coast of Alaska, Icy Cape to Cape Prince of Wales: U.S. Geological Survey Open-File Report 2019–1146, 52 p., https://doi.org/10.3133/ofr20191146.","productDescription":"Report: vi, 52 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-111408","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":399433,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109572.htm"},{"id":370888,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1146/coverthb.jpg"},{"id":370889,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1146/ofr20191146.pdf","text":"Report","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1146"},{"id":370890,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9H1S1PV","linkHelpText":"National assessment of shoreline change—A GIS compilation of updated vector shorelines and associated shoreline change data for the north coast of Alaska, Icy Cape to Cape Prince of Wales"}],"country":"United States","state":"Alaska","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -168.1194,\n              65.5739\n            ],\n            [\n              -160.9839,\n              65.5739\n            ],\n            [\n              -160.9839,\n              70.3322\n            ],\n            [\n              -168.1194,\n              70.3322\n            ],\n            [\n              -168.1194,\n              65.5739\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"http://walrus.wr.usgs.gov/infobank/programs/html/staff2html/staff.html\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"http://walrus.wr.usgs.gov/infobank/programs/html/staff2html/staff.html\">Contact Information</a><br><a href=\"https://walrus.wr.usgs.gov/\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://walrus.wr.usgs.gov/\">Pacific Coastal &amp; Marine 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>Pacific Science Center<br>2885 Mission St.<br>Santa Cruz, CA 95060</p>","tableOfContents":"<p></p><ul><li>Acknowledgments</li><li>Executive Summary</li><li>Introduction</li><li>Previous National and Northwestern Alaska Shoreline Assessments</li><li>Methods of Analyzing Shoreline Change</li><li>Calculation and Interpretation of Shoreline Change Rates</li><li>Results from Analysis of Historical Shoreline Change</li><li>Discussion and Additional Considerations</li><li>References Cited</li></ul><p></p>","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"publishedDate":"2019-12-30","noUsgsAuthors":false,"publicationDate":"2019-12-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Gibbs, Ann E. 0000-0002-0883-3774 agibbs@usgs.gov","orcid":"https://orcid.org/0000-0002-0883-3774","contributorId":2644,"corporation":false,"usgs":true,"family":"Gibbs","given":"Ann","email":"agibbs@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":777820,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Snyder, Alexander G. 0000-0001-6250-4827 agsnyder@usgs.gov","orcid":"https://orcid.org/0000-0001-6250-4827","contributorId":171654,"corporation":false,"usgs":true,"family":"Snyder","given":"Alexander","email":"agsnyder@usgs.gov","middleInitial":"G.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":777821,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Richmond, Bruce M. 0000-0002-0056-5832 brichmond@usgs.gov","orcid":"https://orcid.org/0000-0002-0056-5832","contributorId":2459,"corporation":false,"usgs":true,"family":"Richmond","given":"Bruce","email":"brichmond@usgs.gov","middleInitial":"M.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":777822,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70206261,"text":"sir20195110 - 2019 - Streambed scour evaluations and conditions at selected bridge sites in Alaska, 2016–17","interactions":[],"lastModifiedDate":"2023-04-13T10:56:36.045601","indexId":"sir20195110","displayToPublicDate":"2019-12-30T15:47:16","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2019-5110","displayTitle":"Streambed Scour Evaluations and Conditions at Selected Bridge Sites in Alaska, 2016–17","title":"Streambed scour evaluations and conditions at selected bridge sites in Alaska, 2016–17","docAbstract":"<p>Stream stability, flood frequency, and streambed scour potential were evaluated at 20 Alaskan river- and stream-spanning bridges lacking a quantitative scour analysis or having unknown foundation details. Three of the bridges had been assessed shortly before the study described in this report but were re-assessed using different methods or data. Channel instability related to mining may affect scour at one site, while channel instability related to flow distribution changes can be seen at one site. One bridge was closed because of abutment scour prior to the study. Otherwise, channels generally showed stable bed elevations.</p><p>Contraction and abutment scour were calculated for all 20 bridges, and pier scour was calculated for the 2 bridges that had piers. Vertical contraction (pressure flow) scour was calculated for one site at which the modeled water surface was higher than the superstructure of the bridge. Hydraulic variables for the scour calculations were derived from one-dimensional and two-dimensional hydraulic models of the 1- and 0.2-percent annual exceedance probability floods (also known as the 100- and 500-year floods, respectively). Scour also was calculated for large recorded floods at two sites.</p><p>At many sites, overflow of road approaches relieves the bridge during floods and lessens the potential for scour. Two-dimensional hydraulic models are superior to one-dimensional hydraulic models at distributing flow between bridges, road approaches, and floodplains, and therefore likely produce more reasonable scour values at sites with substantial floodplain flow.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195110","collaboration":"Prepared in cooperation with the Alaska Department of Transportation and Public Facilities","usgsCitation":"Beebee, R.A., Dworsky, K.L., and Knopp, S.J., 2019, Streambed scour evaluations and conditions at selected bridge Sites in Alaska, 2016–17 (version 1.1, April 2023): U.S. Geological Survey Scientific Investigations Report 2019-5110, 32 p., https://doi.org/10.3133/sir20195110.","productDescription":"Report: vi, 32 p.; Data Release","numberOfPages":"32","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-099321","costCenters":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"links":[{"id":399597,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109571.htm"},{"id":370872,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5110/coverthb2.jpg"},{"id":370873,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5110/sir20195110.pdf","text":"Report","size":"2.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019-5110"},{"id":415671,"rank":5,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2019/5110/sir20195110_RevisionHistory.txt","description":"SIR 2019-5110 Version History"},{"id":370874,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9LUTFHZ","linkHelpText":"Tabular input/output data and model files for 19 hydraulic models for streambed scour evaluations at selected bridge sites, Alaska, 2016–17"}],"country":"United States","state":"Alaska","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -155.41259765625,\n              59.01794033995248\n            ],\n            [\n              -144.77783203125,\n              59.01794033995248\n            ],\n            [\n              -144.77783203125,\n              64.97006438589436\n            ],\n            [\n              -155.41259765625,\n              64.97006438589436\n            ],\n            [\n              -155.41259765625,\n              59.01794033995248\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","edition":"Version 1.1: April 2023; Version 1.0: December 2019","contact":"<p><a href=\"https://www.usgs.gov/centers/asc/connect\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov/centers/asc/connect\">Director</a>,<br><a href=\"https://www.usgs.gov/centers/asc/\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov/centers/asc/\">Alaska Science Center</a><br><a href=\"https://www.usgs.gov/\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov/\">U.S. Geological Survey</a><br>4210 University Drive<br>Anchorage, Alaska 99508</p>","tableOfContents":"<p></p><ul><li>Abstract</li><li>Introduction</li><li>Study Approach</li><li>Stream Stability and Geomorphic Assessment</li><li>Flood History and Frequency Analysis</li><li>Hydraulic Model Development</li><li>Stream Bathymetry, Topography, and Bridge Geometry Surveys</li><li>Discharge Measurements for Calibration</li><li>Grain-Size Analysis</li><li>Hydraulic Model Development</li><li>Scour Calculations</li><li>Comparisons of Results for Bridges with Both One-Dimensional and Two-Dimensional Models</li><li>Summary and Conclusions</li><li>Acknowledgments</li><li>References Cited</li><li>Glossary</li><li>Appendix 1. Stream Stability Cross Sections</li></ul><p></p>","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"publishedDate":"2019-12-30","revisedDate":"2023-04-12","noUsgsAuthors":false,"publicationDate":"2019-12-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Beebee, Robin A. 0000-0002-2976-7294 rbeebee@usgs.gov","orcid":"https://orcid.org/0000-0002-2976-7294","contributorId":5778,"corporation":false,"usgs":true,"family":"Beebee","given":"Robin","email":"rbeebee@usgs.gov","middleInitial":"A.","affiliations":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"preferred":true,"id":773964,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dworsky, Karenth L. 0000-0002-3287-6934 kdworsky@usgs.gov","orcid":"https://orcid.org/0000-0002-3287-6934","contributorId":200851,"corporation":false,"usgs":true,"family":"Dworsky","given":"Karenth","email":"kdworsky@usgs.gov","middleInitial":"L.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"preferred":false,"id":773965,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Knopp, Schyler J. 0000-0002-3750-1373 sknopp@usgs.gov","orcid":"https://orcid.org/0000-0002-3750-1373","contributorId":200852,"corporation":false,"usgs":true,"family":"Knopp","given":"Schyler","email":"sknopp@usgs.gov","middleInitial":"J.","affiliations":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"preferred":false,"id":773966,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70207149,"text":"ofr20191138 - 2019 - DNA fingerprinting of Southern Mule Deer (Odocoileus hemionus fuliginatus) in North San Diego County, California (2018-19)","interactions":[],"lastModifiedDate":"2019-12-31T09:15:01","indexId":"ofr20191138","displayToPublicDate":"2019-12-30T15:43:40","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2019-1138","displayTitle":"DNA Fingerprinting of Southern Mule Deer (<i>Odocoileus hemionus fuliginatus</i>) in North San Diego County, California (2018–19)","title":"DNA fingerprinting of Southern Mule Deer (Odocoileus hemionus fuliginatus) in North San Diego County, California (2018-19)","docAbstract":"<p>Throughout the western United States, efforts are underway to better understand and preserve migration and movement corridors for mule deer and other big game and to minimize the impacts of development and other land-use change on populations. San Diego County is home to a unique non-migratory subspecies of mule deer, the Southern mule deer (<i>Odocoileus hemionus fuliginatus</i>; herein referred to as “mule deer”). Because it is the only large herbivorous mammal in San Diego, connectivity among mule deer groups is an important indicator of functional connectivity throughout San Diego County urban preserves and has therefore been monitored within central and eastern San Diego County using DNA fingerprinting since 2005. To continue this effort and to assess genetic connectivity in north San Diego County (herein “North County”), we genotyped scat samples from preserves in the area and tissue samples from Marine Corps Base Camp Pendleton (MCBCP). We used non-invasive capture/recapture analyses and pedigree analyses for assessing short-term movement and population clustering analyses to assess gene flow in North County. Additionally, we performed similar analyses on the combined San Diego County dataset, which was composed of the North County dataset collected for this study and a previously collected dataset from central and eastern San Diego County. Using recapture data, we found multiple instances of mule deer crossing roads in urban North County preserves, with several of these events occurring in areas where there are underpasses and culverts known to be used by mule deer. Corroborating previous studies in the region and statewide, pedigree and population structure analyses support the presence of two genetic clusters for mule deer in San Diego County—the “Coastal” and “Inland/Mountain” clusters. Low estimates of effective population size, especially in the Coastal cluster, suggest that to further understand potential vulnerabilities of mule deer in this region, it is important to continue to monitor connectivity, in particular, at the boundary between these two clusters.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191138","usgsCitation":"Mitelberg, A., Smith, J.G., and Vandergast, A.G., 2019, DNA Fingerprinting of Southern mule deer (<i>Odocoileus hemionus fuliginatus</i>) in north San Diego County, California (2018–19): U.S. Geological Survey Open-File Report 2019–1138, 25 p., https://doi.org/10.3133/ofr20191138.","productDescription":"vi, 25 p.","numberOfPages":"25","onlineOnly":"Y","ipdsId":"IP-112707","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":437245,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9YXWXA9","text":"USGS data release","linkHelpText":"Microsatellite Genetic Marker Genotypes from Southern Mule Deer (Odocoileus hemionus fuliginatus) Sampled in San Diego County, California"},{"id":370869,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1138/ofr20191138.pdf","text":"Report","size":"31 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":370868,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1138/coverthb.jpg"}],"country":"United States","state":"California","county":"San Diego County","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -117.31201171875001,\n              32.713355353177555\n            ],\n            [\n              -116.05957031249999,\n              32.713355353177555\n            ],\n            [\n              -116.05957031249999,\n              33.25706340236547\n            ],\n            [\n              -117.31201171875001,\n              33.25706340236547\n            ],\n            [\n              -117.31201171875001,\n              32.713355353177555\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"https://www.usgs.gov/centers/werc/connect\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov/centers/werc/connect\">Director</a>,<br><a href=\"https://www.usgs.gov/centers/werc\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov/centers/werc\">Western Ecological Research Center</a><br><a href=\"https://www.usgs.gov/\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov/\">U.S. Geological Survey</a><br>3020 State University Drive East<br>Sacramento, California 95819</p>","tableOfContents":"<p></p><ul><li>Abstract</li><li>Introduction</li><li>Methods</li><li>Results</li><li>Discussion</li><li>References Cited</li><li>Appendix 1</li></ul><p></p>","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"publishedDate":"2019-12-30","noUsgsAuthors":false,"publicationDate":"2019-12-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Mitelberg, Anna 0000-0002-3309-9946 amitelberg@usgs.gov","orcid":"https://orcid.org/0000-0002-3309-9946","contributorId":218945,"corporation":false,"usgs":true,"family":"Mitelberg","given":"Anna","email":"amitelberg@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":776977,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smith, Julia G. 0000-0001-9841-1809","orcid":"https://orcid.org/0000-0001-9841-1809","contributorId":221086,"corporation":false,"usgs":true,"family":"Smith","given":"Julia","email":"","middleInitial":"G.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":776978,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Vandergast, Amy G. 0000-0002-7835-6571 avandergast@usgs.gov","orcid":"https://orcid.org/0000-0002-7835-6571","contributorId":3963,"corporation":false,"usgs":true,"family":"Vandergast","given":"Amy","email":"avandergast@usgs.gov","middleInitial":"G.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":776976,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70207221,"text":"ofr20191108 - 2019 - Economic effects of wildfire risk reduction and source water protection projects in the Rio Grande River Basin in northern New Mexico and southern Colorado","interactions":[],"lastModifiedDate":"2022-04-21T18:50:28.74984","indexId":"ofr20191108","displayToPublicDate":"2019-12-30T11:15:00","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2019-1108","displayTitle":"Economic Effects of Wildfire Risk Reduction and Source Water Protection Projects in the Rio Grande River Basin in Northern New Mexico and Southern Colorado","title":"Economic effects of wildfire risk reduction and source water protection projects in the Rio Grande River Basin in northern New Mexico and southern Colorado","docAbstract":"<p>Investments in landscape-scale restoration and fuels management projects can protect publicly managed trusts, enhance public health and safety, and help to preserve the many environmental goods and services enjoyed by the public. These investments can also support jobs and generate business sales activities within nearby local economies. This report investigates how investments made by the Rio Grande Water Fund (RGWF) on wildfire risk reduction and source water protection projects in northern New Mexico and southern Colorado affect local economic activity. To implement these projects, the RGWF spent a total of <span>$</span>855,000 in 2018 on contractors located in the Western States regional economy. Including direct and secondary effects, these expenditures supported an estimated 22 jobs, <span>$</span>1,089,000 in labor income, <span>$</span>1,324,000 in value added, and <span>$</span>1,907,000 in economic output in the 17 Western States economy. The majority (73 percent or <span>$</span>623,000) of these expenditures were made by hiring local businesses operating within a 13-county region in northern New Mexico and southern Colorado that comprises the RGWF project area. Including direct and secondary effects, local expenditures support an estimate 15 jobs, <span>$</span>676,000 in labor income, <span>$</span>791,000 in value added, and <span>$</span>1,120,000 in economic output within the 13-county RGWF project area. These results demonstrate how investments in wildfire risk reduction and source water protection projects can support jobs and livelihoods, small businesses, and rural economies in the Mountain West.</p>","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191108","collaboration":"Prepared in cooperation with The Nature Conservancy","usgsCitation":"Huber, C., Cullinane Thomas, C., Meldrum, J.R., Meier, R., and Bassett, S., 2019, Economic effects of wildfire risk reduction and source water protection projects in the Rio Grande River Basin in northern New Mexico and southern Colorado: U.S. Geological Survey Open-File Report 2019–1108, 8 p., https://doi.org/10.3133/ofr20191108.","productDescription":"iv, 8 p.","onlineOnly":"Y","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":399416,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109581.htm"},{"id":370215,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1108/ofr20191108.pdf","text":"Report","size":"7.71 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1108"},{"id":370214,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1108/coverthb.jpg"}],"country":"United States","state":"Colorado, New Mexico","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -107.6408,\n              34.2403\n            ],\n            [\n              -103.6667,\n              34.2403\n            ],\n            [\n              -103.6667,\n              37.3417\n            ],\n            [\n              -107.6408,\n              37.3417\n            ],\n            [\n              -107.6408,\n              34.2403\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p>Director,&nbsp;<a href=\"https://www.usgs.gov/fort/\" data-mce-href=\"https://www.usgs.gov/fort/\">Fort Collins Science Center</a><br>U.S. Geological Survey<br>2150 Centre Ave., Building C<br>Fort Collins, CO 80526-8118</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Executive Summary</li><li>Introduction</li><li>Results</li><li>Conclusions</li><li>References Cited</li></ul>","publishedDate":"2019-12-30","noUsgsAuthors":false,"publicationDate":"2019-12-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Huber, Christopher 0000-0001-8446-8134 chuber@usgs.gov","orcid":"https://orcid.org/0000-0001-8446-8134","contributorId":127600,"corporation":false,"usgs":true,"family":"Huber","given":"Christopher","email":"chuber@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":777333,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cullinane Thomas, Catherine 0000-0001-8168-1271 ccullinanethomas@usgs.gov","orcid":"https://orcid.org/0000-0001-8168-1271","contributorId":141097,"corporation":false,"usgs":true,"family":"Cullinane Thomas","given":"Catherine","email":"ccullinanethomas@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":777334,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Meldrum, James R. 0000-0001-5250-3759 jmeldrum@usgs.gov","orcid":"https://orcid.org/0000-0001-5250-3759","contributorId":195484,"corporation":false,"usgs":true,"family":"Meldrum","given":"James","email":"jmeldrum@usgs.gov","middleInitial":"R.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":777335,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Meier, Rachel","contributorId":221199,"corporation":false,"usgs":false,"family":"Meier","given":"Rachel","email":"","affiliations":[{"id":7041,"text":"The Nature Conservancy","active":true,"usgs":false}],"preferred":false,"id":777336,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bassett, Steven 0000-0002-3826-3960","orcid":"https://orcid.org/0000-0002-3826-3960","contributorId":221200,"corporation":false,"usgs":false,"family":"Bassett","given":"Steven","email":"","affiliations":[{"id":7041,"text":"The Nature Conservancy","active":true,"usgs":false}],"preferred":false,"id":778675,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70203456,"text":"sir20195001 - 2019 - Severity and extent of alterations to natural streamflow regimes based on hydrologic metrics in the conterminous United States, 1980–2014","interactions":[],"lastModifiedDate":"2022-04-22T21:11:02.782667","indexId":"sir20195001","displayToPublicDate":"2019-12-30T07:30:00","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2019-5001","displayTitle":"Severity and Extent of Alterations to Natural Streamflow Regimes Based on Hydrologic Metrics in the Conterminous United States, 1980-2014","title":"Severity and extent of alterations to natural streamflow regimes based on hydrologic metrics in the conterminous United States, 1980–2014","docAbstract":"Alteration of the natural streamflow regime by land and water management, such as land-cover change and dams, is associated with aquatic ecosystem degradation. The severity and geographic extent of streamflow alteration at regional and national scales, however, remain largely unquantified. The primary goal of this study is to characterize the severity and extent of alterations to natural streamflow regimes for 1980–2014 based on hydrologic metrics at 3,355 U.S. Geological Survey streamgages in the conterminous United States. Twelve hydrologic metrics with known relevance to aquatic ecosystem health were used to characterize the streamflow regime. Alterations to the 12 hydrologic metrics were quantified by taking ratios of the metrics calculated from observed daily streamflow records divided by the same metrics predicted for natural conditions by random forest statistical models. Some level of streamflow alteration (diminishment or inflation of hydrologic metrics) compared to natural conditions was indicated at about 80 percent of the assessed streamgages across the conterminous United States. The severity of alteration differed among ecoregions because of differences in dominant land and water management practices. Finally, when compared over the period 1980–2014, climate variability generally played a minor role in the alteration of streamflows across the United States when compared to the effects of land and water management.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195001","usgsCitation":"Eng, K., Carlisle, D.M., Grantham, T.E., Wolock, D.M., and Eng, R.L., 2019, Severity and extent of alterations to natural streamflow regimes based on hydrologic metrics in the conterminous United States, 1980–2014: U.S. Geological Survey Scientific Investigations Report 2019–5001, 25 p., https://doi.org/10.3133/sir20195001.","productDescription":"Report: iv, 25 p.; Data Release","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-099228","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":370492,"rank":4,"type":{"id":22,"text":"Related 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-102.216796875,\n              29.22889003019423\n            ],\n            [\n              -97.55859375,\n              25.48295117535531\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p>Chief, <a href=\"mailto: gs_b17c@usgs.gov\" data-mce-href=\"mailto: gs_b17c@usgs.gov\">Analysis and Prediction Branch</a><br>Integrated Modeling and Prediction Division<br>Water Resources Mission Area<br>U.S. Geological Survey, Mail Stop 415<br>12201 Sunrise Valley Drive<br>Reston, VA 20192</p>","tableOfContents":"<ul><li>Abstract</li><li>Introduction</li><li>Methods</li><li>Severity and Extent of Alterations to Natural Streamflow Regimes</li><li>Synthesis of Alterations to Natural Streamflow Regimes</li><li>Summary</li></ul>","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2019-12-26","noUsgsAuthors":false,"publicationDate":"2019-12-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Eng, Ken 0000-0001-6838-5849 keng@usgs.gov","orcid":"https://orcid.org/0000-0001-6838-5849","contributorId":3580,"corporation":false,"usgs":true,"family":"Eng","given":"Ken","email":"keng@usgs.gov","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":762759,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Carlisle, Daren M. 0000-0002-7367-348X dcarlisle@usgs.gov","orcid":"https://orcid.org/0000-0002-7367-348X","contributorId":513,"corporation":false,"usgs":true,"family":"Carlisle","given":"Daren","email":"dcarlisle@usgs.gov","middleInitial":"M.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true}],"preferred":true,"id":762760,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Grantham, Theodore E.","contributorId":198855,"corporation":false,"usgs":false,"family":"Grantham","given":"Theodore E.","affiliations":[{"id":6643,"text":"University of California - Berkeley","active":true,"usgs":false}],"preferred":false,"id":762761,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wolock, David M. 0000-0002-6209-938X dwolock@usgs.gov","orcid":"https://orcid.org/0000-0002-6209-938X","contributorId":540,"corporation":false,"usgs":true,"family":"Wolock","given":"David","email":"dwolock@usgs.gov","middleInitial":"M.","affiliations":[{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":true,"id":762762,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Eng, Rosaly L.","contributorId":215594,"corporation":false,"usgs":false,"family":"Eng","given":"Rosaly","email":"","middleInitial":"L.","affiliations":[{"id":39290,"text":"Oakton High School, VA","active":true,"usgs":false}],"preferred":false,"id":762763,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70211341,"text":"70211341 - 2019 - Post-collapse gravity increase at the summit of Kīlauea Volcano, Hawaiʻi","interactions":[],"lastModifiedDate":"2020-07-27T15:04:13.162493","indexId":"70211341","displayToPublicDate":"2019-12-28T10:01:56","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Post-collapse gravity increase at the summit of Kīlauea Volcano, Hawaiʻi","docAbstract":"We conducted gravity surveys of the summit area of Kīlauea Volcano, Hawaiʻi, in November 2018 and March 2019, with the goal of determining whether there was any mass change at depth following the volcano's May–August 2018 caldera collapse. Surface deformation between the two surveys was minimal, but we measured a gravity increase (maximum 44 μGal) centered on the caldera that can be modeled as mass accumulation in a region ~1 km beneath the surface. We interpret this mass increase to be mostly magma accumulation in void space that was created during the summit collapse. Caldera uplift was evident by April 2019, indicating that the magma volume had reached a point where pressurization could be sustained. Modeled gravity change suggests a maximum magma storage rate at Kīlauea's summit during November 2018 to March 2019 that is much less than the pre‐2018 magma supply rate to the volcano.","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2019GL084901","usgsCitation":"Poland, M.P., de Zeeuw-van Dalfsen, E., Bagnardi, M., and Johanson, I.A., 2019, Post-collapse gravity increase at the summit of Kīlauea Volcano, Hawaiʻi: Geophysical Research Letters, v. 46, no. 24, p. 14430-14439, https://doi.org/10.1029/2019GL084901.","productDescription":"10 p.","startPage":"14430","endPage":"14439","ipdsId":"IP-111004","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":458882,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2019gl084901","text":"Publisher Index Page"},{"id":376713,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Kīlauea volcano","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -155.29483795166016,\n              19.39212483416422\n            ],\n            [\n              -155.23441314697266,\n              19.39212483416422\n            ],\n            [\n              -155.23441314697266,\n              19.44134189745716\n            ],\n            [\n              -155.29483795166016,\n              19.44134189745716\n            ],\n            [\n              -155.29483795166016,\n              19.39212483416422\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"46","issue":"24","noUsgsAuthors":false,"publicationDate":"2019-12-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Poland, Michael P. 0000-0001-5240-6123 mpoland@usgs.gov","orcid":"https://orcid.org/0000-0001-5240-6123","contributorId":146118,"corporation":false,"usgs":true,"family":"Poland","given":"Michael","email":"mpoland@usgs.gov","middleInitial":"P.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":793925,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"de Zeeuw-van Dalfsen, Elske 0000-0003-2527-4932","orcid":"https://orcid.org/0000-0003-2527-4932","contributorId":217967,"corporation":false,"usgs":false,"family":"de Zeeuw-van Dalfsen","given":"Elske","email":"","affiliations":[{"id":39727,"text":"KNMI","active":true,"usgs":false}],"preferred":false,"id":793926,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bagnardi, Marco","contributorId":124560,"corporation":false,"usgs":false,"family":"Bagnardi","given":"Marco","affiliations":[{"id":5112,"text":"University of Miami","active":true,"usgs":false}],"preferred":false,"id":793927,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Johanson, Ingrid A. 0000-0002-6049-2225","orcid":"https://orcid.org/0000-0002-6049-2225","contributorId":215613,"corporation":false,"usgs":true,"family":"Johanson","given":"Ingrid","email":"","middleInitial":"A.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":793928,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70209964,"text":"70209964 - 2019 - Catastrophic landscape modification from a massive landslide tsunami in Taan Fiord, Alaska","interactions":[],"lastModifiedDate":"2020-05-07T12:51:41.964537","indexId":"70209964","displayToPublicDate":"2019-12-28T07:40:39","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1801,"text":"Geomorphology","active":true,"publicationSubtype":{"id":10}},"title":"Catastrophic landscape modification from a massive landslide tsunami in Taan Fiord, Alaska","docAbstract":"The October 17th, 2015 Taan Fiord landslide and tsunami generated a runup of 193 m, nearly an order of magnitude greater than most previously surveyed tsunamis. To date, most post-tsunami surveys are from earthquake-generated tsunamis and the geomorphic signatures of landslide tsunamis or their potential for preservation are largely uncharacterized. Additionally, clear modifications described during previous post-tsunami surveys are often ephemeral and unlikely to be preserved. Documented geomorphic modifications of several low gradient fan deltas within Taan Fiord make it an excellent laboratory for characterizing signatures of a landslide tsunami event. Geomorphic changes to fan deltas in Taan Fiord caused by the landslide-generated tsunami included complete vegetation loss over more than 0.6 km2 of fan surfaces, formation of steep fan front scarps up to 10 m high, extensive local alterations of fan topography, and formation of new tsunami return-flow channels. Two relatively stable fan deltas in Taan Fiord were heavily vegetated prior to the Taan event and may preserve features of tsunami modification for decades to centuries. If this is the case, fan deltas may be a previously unrecognized location for preservation of tsunami signatures in the recent past. Fans in poorly monitored regions, such as Greenland, could thus hold evidence of previously unidentified recent landslide tsunami events.","language":"English","publisher":"Elsevier","doi":"10.1016/j.geomorph.2019.107029","collaboration":"","usgsCitation":"Bloom, C.K., MacInnes, B., Higman, B., Shugar, D., Venditti, J., Richmond, B.M., and Bilderback, E.L., 2019, Catastrophic landscape modification from a massive landslide tsunami in Taan Fiord, Alaska: Geomorphology, v. 353, 107029, 12 p., https://doi.org/10.1016/j.geomorph.2019.107029.","productDescription":"107029, 12 p.","ipdsId":"IP-109761","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":374532,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Taan Fiord","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -141.74560546874997,\n              59.833775202184206\n            ],\n            [\n              -141.064453125,\n              59.833775202184206\n            ],\n            [\n              -141.064453125,\n              60.261617082844616\n            ],\n            [\n              -141.74560546874997,\n              60.261617082844616\n            ],\n            [\n              -141.74560546874997,\n              59.833775202184206\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"353","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Bloom, Colin K","contributorId":224586,"corporation":false,"usgs":false,"family":"Bloom","given":"Colin","email":"","middleInitial":"K","affiliations":[{"id":40892,"text":"Central Washington University Dept. of Geological Sciences, Ellensburg, WA, USA","active":true,"usgs":false}],"preferred":false,"id":788608,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"MacInnes, Breanyn","contributorId":192477,"corporation":false,"usgs":false,"family":"MacInnes","given":"Breanyn","email":"","affiliations":[],"preferred":false,"id":788609,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Higman, Bretwood","contributorId":224587,"corporation":false,"usgs":false,"family":"Higman","given":"Bretwood","affiliations":[{"id":40893,"text":"Ground Truth Trekking, Seldovia, AK, USA","active":true,"usgs":false}],"preferred":false,"id":788610,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shugar, Dan H. 0000-0002-6279-8420","orcid":"https://orcid.org/0000-0002-6279-8420","contributorId":224588,"corporation":false,"usgs":false,"family":"Shugar","given":"Dan H.","affiliations":[{"id":40894,"text":"University of Calgary, Calgary, Alberta, Canada","active":true,"usgs":false}],"preferred":false,"id":788611,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Venditti, Jeremy G. 0000-0002-2876-4251","orcid":"https://orcid.org/0000-0002-2876-4251","contributorId":197757,"corporation":false,"usgs":false,"family":"Venditti","given":"Jeremy G.","affiliations":[],"preferred":false,"id":788612,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Richmond, Bruce M. 0000-0002-0056-5832 brichmond@usgs.gov","orcid":"https://orcid.org/0000-0002-0056-5832","contributorId":2459,"corporation":false,"usgs":true,"family":"Richmond","given":"Bruce","email":"brichmond@usgs.gov","middleInitial":"M.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":788638,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bilderback, Eric L.","contributorId":224589,"corporation":false,"usgs":false,"family":"Bilderback","given":"Eric","email":"","middleInitial":"L.","affiliations":[{"id":40895,"text":"National Park Service, Geologic Resources Division, Denver, CO, USA","active":true,"usgs":false}],"preferred":false,"id":788614,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70209222,"text":"70209222 - 2019 - Some experiments in extreme-value statistical modeling of magnetic superstorm intensities","interactions":[],"lastModifiedDate":"2020-03-24T13:54:18","indexId":"70209222","displayToPublicDate":"2019-12-27T13:53:08","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3456,"text":"Space Weather","active":true,"publicationSubtype":{"id":10}},"title":"Some experiments in extreme-value statistical modeling of magnetic superstorm intensities","docAbstract":"In support of projects for forecasting and mitigating the deleterious effects of extreme space-weather storms, an examination is made of the intensities of magnetic superstorms recorded in the Dst index time series (1957-2016). Modified peak-over-threshold and solar-cycle, block-maximum sampling of the Dst time series are performed to obtain compi-lations of storm-maximum −Dstm intensity values. Lognormal, upper-limit lognormal, generalized Pareto, and generalized extreme-value model distributions are fitted to the−Dstm data using a maximum-likelihood algorithm. All four candidate models provide good representations of the data. Comparisons of the statistical significance and good-ness of fits of the various models gives no clear indication as to which model is best. The statistical models are used to extrapolate to extreme-value intensities, such as would be expected (on average) to occur once per century. An upper-limit lognormal fit to peak-over-threshold −Dstm data above a superstorm threshold of 283 nT gives a 100-year ex-trapolated intensity of 542 nT and a 68% confidence interval (obtained by bootstrap re-sampling) of [466, 583] nT. An upper-limit lognormal fit to solar-cycle, block-maximum−DstBM data gives a 9-solar-cycle (approximately 100-year) extrapolated intensity of 553 nT. The Dst data are found to be insufficient for providing usefully accurate esti-mates of a statistically theoretical upper limit for magnetic storm intensity. Secular change in storm intensities is noted, as is a need for improved estimates of pre-1957 magnetic storm intensities.","language":"English","publisher":"Wiley","doi":"10.1029/2019SW002255","usgsCitation":"Love, J.J., 2019, Some experiments in extreme-value statistical modeling of magnetic superstorm intensities: Space Weather, v. 18, no. 1, e2019SW002255, https://doi.org/10.1029/2019SW002255.","productDescription":"e2019SW002255","ipdsId":"IP-113786","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":458884,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2019sw002255","text":"Publisher Index Page"},{"id":373485,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"18","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2020-01-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Love, Jeffrey J. 0000-0002-3324-0348 jlove@usgs.gov","orcid":"https://orcid.org/0000-0002-3324-0348","contributorId":760,"corporation":false,"usgs":true,"family":"Love","given":"Jeffrey","email":"jlove@usgs.gov","middleInitial":"J.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":785445,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70226995,"text":"70226995 - 2019 - Age and growth of stocked juvenile Shoal Bass in a tailwater: Environmental variation and accuracy of daily age estimates","interactions":[],"lastModifiedDate":"2021-12-27T14:51:51.062894","indexId":"70226995","displayToPublicDate":"2019-12-27T08:49:49","publicationYear":"2019","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":"Age and growth of stocked juvenile Shoal Bass in a tailwater: Environmental variation and accuracy of daily age estimates","docAbstract":"<div class=\"abstract toc-section abstract-type-\"><div class=\"abstract-content\"><p>Otolith microanalysis is often used to assess population age structure and growth of fishes during their early stages. Shoal Bass<span>&nbsp;</span><i>Micropterus cataractae</i><span>&nbsp;</span>is a recently described species of conservation concern and little is known regarding factors affecting their recruitment. In 2004, Georgia Department of Natural Resources (GADNR) and the US National Park Service (NPS) stocked Shoal Bass marked with oxytetracycline (OTC) in the Chattahoochee River near Atlanta, Georgia in an effort to restore this population, creating known-age fish to examine the effect of environment on daily age accuracy. We obtained samples of stocked juvenile (&lt;150 mm) Shoal Bass from standard monitoring that occurred approximately 30–60 days after stocking in the Chattahoochee River to 1) validate daily rings for estimating age, hatch dates, and growth rates for stocked age-0 Shoal Bass, and 2) evaluate the effect of habitat (location) on age bias. Shoal Bass otoliths were examined for OTC marks and daily rings were counted in reference to OTC marks to assess age estimation accuracy. Age estimation accuracy ranged from -2 to -25 days and was influenced by the environment where Shoal Bass were captured, with greater inaccuracy in colder water temperatures. Fish collected from locations with colder temperatures displayed closer spacing of daily rings, potentially leading to greater underestimation of age. Growth rates of stocked Shoal Bass, corrected for age estimation error, ranged from 0.5 mm/day to 0.8 mm/day. This study demonstrates the effect of environmental variability on age inaccuracy and subsequent interpretation of results. Incorporating methods to assess age estimation accuracy is needed to understand interspecific differences in recruitment among black bass species in the variety of natural and human-modified environments they inhabit.</p></div></div><div id=\"figure-carousel-section\"><br></div>","language":"English","publisher":"PLoS","doi":"10.1371/journal.pone.0224018","usgsCitation":"Long, J.M., and Porta, M., 2019, Age and growth of stocked juvenile Shoal Bass in a tailwater: Environmental variation and accuracy of daily age estimates: PLoS ONE, v. 14, no. 10, e0224018, 15 p., https://doi.org/10.1371/journal.pone.0224018.","productDescription":"e0224018, 15 p.","ipdsId":"IP-106470","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":458885,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0224018","text":"Publisher Index Page"},{"id":393419,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Georgia","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -84.957275390625,\n              33.247875947924385\n            ],\n            [\n              -83.902587890625,\n              33.247875947924385\n            ],\n            [\n              -83.902587890625,\n              34.261756524459805\n            ],\n            [\n              -84.957275390625,\n              34.261756524459805\n            ],\n            [\n              -84.957275390625,\n              33.247875947924385\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"14","issue":"10","noUsgsAuthors":false,"publicationDate":"2019-10-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Long, James M. 0000-0002-8658-9949 jmlong@usgs.gov","orcid":"https://orcid.org/0000-0002-8658-9949","contributorId":3453,"corporation":false,"usgs":true,"family":"Long","given":"James","email":"jmlong@usgs.gov","middleInitial":"M.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":829128,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Porta, M. J.","contributorId":264714,"corporation":false,"usgs":false,"family":"Porta","given":"M. J.","affiliations":[{"id":27443,"text":"Oklahoma Department of Wildlife Conservation","active":true,"usgs":false}],"preferred":false,"id":829129,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70209066,"text":"70209066 - 2019 - Effect of growth rate on transcriptomic responses to immune stimulation in wild-type, domesticated, and GH-transgenic coho salmon","interactions":[],"lastModifiedDate":"2020-03-13T06:58:32","indexId":"70209066","displayToPublicDate":"2019-12-27T06:57:30","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":956,"text":"BMC Genomics","active":true,"publicationSubtype":{"id":10}},"title":"Effect of growth rate on transcriptomic responses to immune stimulation in wild-type, domesticated, and GH-transgenic coho salmon","docAbstract":"Background\nTranscriptomic responses to immune stimulation were investigated in coho salmon (Oncorhynchus kisutch) with distinct growth phenotypes. Wild-type fish were contrasted to strains with accelerated growth arising either from selective breeding (i.e. domestication) or genetic modification. Such distinct routes to accelerated growth may have unique implications for relationships and/or trade-offs between growth and immune function.\n\nResults\nRNA-Seq was performed on liver and head kidney in four ‘growth response groups’ injected with polyinosinic-polycytidylic acid (Poly I:C; viral mimic), peptidoglycan (PGN; bacterial mimic) or PBS (control). These groups were: 1) ‘W’: wild-type, 2) ‘TF’: growth hormone (GH) transgenic salmon with ~ 3-fold higher growth-rate than W, 3) ‘TR’: GH transgenic fish ration restricted to possess a growth-rate equal to W, and 4) ‘D’: domesticated non-transgenic fish showing growth-rate intermediate to W and TF. D and TF showed a higher similarity in transcriptomic response compared to W and TR. Several immune genes showed constitutive expression differences among growth response groups, including perforin 1 and C-C motif chemokine 19-like. Among the affected immune pathways, most were up-regulated by Poly I:C and PGN. In response to PGN, the c-type lectin receptor signalling pathway responded uniquely in TF and TR. In response to stimulation with both immune mimics, TR responded more strongly than other groups. Further, group-specific pathway responses to PGN stimulation included NOD-like receptor signalling in W and platelet activation in TR. TF consistently showed the most attenuated immune response relative to W, and more DEGs were apparent in TR than TF and D relative to W, suggesting that a non-satiating ration coupled with elevated circulating GH levels may cause TR to possess enhanced immune capabilities. Alternatively, TF and D salmon are prevented from acquiring the same level of immune response as TR due to direction of energy to high overall somatic growth. Further study of the effects of ration restriction in growth-modified fishes is warranted.\n\nConclusions\nThese findings improve our understanding of the pleiotropic effects of growth modification on the immunological responses of fish, revealing unique immune pathway responses depending on the mechanism of growth acceleration and nutritional availability.","language":"English","publisher":"Springer","doi":"10.1186/s12864-019-6408-4","usgsCitation":"Kim, J., Macqueen, D.J., Winton, J., Hansen, J.D., Park, H., and Devlin, R.H., 2019, Effect of growth rate on transcriptomic responses to immune stimulation in wild-type, domesticated, and GH-transgenic coho salmon: BMC Genomics, v. 20, 1024, 16 p., https://doi.org/10.1186/s12864-019-6408-4.","productDescription":"1024, 16 p.","ipdsId":"IP-110928","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":458889,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s12864-019-6408-4","text":"Publisher Index Page"},{"id":373229,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"20","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2019-12-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Kim, Jin-Hyoung","contributorId":223257,"corporation":false,"usgs":false,"family":"Kim","given":"Jin-Hyoung","email":"","affiliations":[{"id":40694,"text":"Fisheries and Oceans Canada, 4160 Marine Drive, West Vancouver, BC, V7V 1N6 Canada","active":true,"usgs":false}],"preferred":false,"id":784693,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Macqueen, Daniel J","contributorId":223258,"corporation":false,"usgs":false,"family":"Macqueen","given":"Daniel","email":"","middleInitial":"J","affiliations":[{"id":40695,"text":"The Roslin Institute and Royal (Dick) School of Veterinary Studies, The University of Edinburgh, Midlothian, EH25 9RG, United Kingdom","active":true,"usgs":false}],"preferred":false,"id":784694,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Winton, James 0000-0002-3505-5509 jwinton@usgs.gov","orcid":"https://orcid.org/0000-0002-3505-5509","contributorId":179330,"corporation":false,"usgs":true,"family":"Winton","given":"James","email":"jwinton@usgs.gov","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":784695,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hansen, John D. 0000-0002-3006-2734 jhansen@usgs.gov","orcid":"https://orcid.org/0000-0002-3006-2734","contributorId":3440,"corporation":false,"usgs":true,"family":"Hansen","given":"John","email":"jhansen@usgs.gov","middleInitial":"D.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":784696,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Park, Hyun","contributorId":223261,"corporation":false,"usgs":false,"family":"Park","given":"Hyun","email":"","affiliations":[{"id":40696,"text":"Korea Polar Research Institute, Unit of Polar Genomics, 26 Sondomirae-ro, Yeonsu-gu, Incheon 21990, Korea","active":true,"usgs":false}],"preferred":false,"id":784697,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Devlin, Robert H","contributorId":223262,"corporation":false,"usgs":false,"family":"Devlin","given":"Robert","email":"","middleInitial":"H","affiliations":[{"id":40694,"text":"Fisheries and Oceans Canada, 4160 Marine Drive, West Vancouver, BC, V7V 1N6 Canada","active":true,"usgs":false}],"preferred":false,"id":784698,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70227764,"text":"70227764 - 2019 - A seasonal population matrix model of the Caribbean Red-tailed Hawk Buteo jamaicensis jamaicensis in eastern Puerto Rico","interactions":[],"lastModifiedDate":"2022-01-28T12:58:55.248676","indexId":"70227764","displayToPublicDate":"2019-12-27T06:56:17","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1961,"text":"Ibis","active":true,"publicationSubtype":{"id":10}},"title":"A seasonal population matrix model of the Caribbean Red-tailed Hawk Buteo jamaicensis jamaicensis in eastern Puerto Rico","docAbstract":"<div class=\"abstract-group\"><div class=\"article-section__content en main\"><p>Reliable estimates of life history parameters and their functional role in animal population trajectories are critical, yet often missing, components in conservation and management. We developed seasonal matrix population models of the Red-tailed Hawk<span>&nbsp;</span><i>Buteo jamaicensis jamaicensis</i><span>&nbsp;</span>in the upper and lower forests of the Luquillo Mountains, Puerto Rico, to describe the influence of early life stages (nestling and clutch survival) on population growth. Modelled populations exhibited positive discrete rates of growth in forests above 400&nbsp;m (<i>λ</i><span>&nbsp;</span>highlands&nbsp;=&nbsp;1.05) and in forests below 400&nbsp;m (<i>λ</i><span>&nbsp;</span>lowlands&nbsp;=&nbsp;1.27) of the Luquillo Mountains. Further, adult survival was the parameter with the highest proportional effect and direct contribution to growth of the population. Besides survival of adults, our results identified that nestling survival had the second greatest influence on<span>&nbsp;</span><i>λ</i>, stressing the importance of this life stage for the population growth rate of Red-tailed Hawks in our study area. Seasonal matrices are not commonly used to describe population dynamics of birds. However, these may be a useful tool to analyse the influence of life stages in the annual cycle to better address conservation and management needs, especially for species inhabiting oceanic islands.</p></div></div>","language":"English","publisher":"Wiley","doi":"10.1111/ibi.12703","usgsCitation":"Gallardo, J.C., Vilella, F., and Colvin, M., 2019, A seasonal population matrix model of the Caribbean Red-tailed Hawk Buteo jamaicensis jamaicensis in eastern Puerto Rico: Ibis, v. 161, no. 2, p. 459-466, https://doi.org/10.1111/ibi.12703.","productDescription":"8 p.","startPage":"459","endPage":"466","ipdsId":"IP-091998","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":395037,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Puerto 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State University","active":true,"usgs":false}],"preferred":false,"id":832100,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70209624,"text":"70209624 - 2019 - Facilitated adaptation for conservation – Can gene editing save Hawaii's endangered birds from climate driven avian malaria?","interactions":[],"lastModifiedDate":"2020-05-04T18:25:45.845802","indexId":"70209624","displayToPublicDate":"2019-12-26T07:06:42","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1015,"text":"Biological Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Facilitated adaptation for conservation – Can gene editing save Hawaii's endangered birds from climate driven avian malaria?","docAbstract":"Avian malaria has played a significant role in causing extinctions, population declines, and limiting the elevational distribution of Hawaiian honeycreepers. Most threatened and endangered honeycreepers only exist in high-elevation forests where the risk of malaria infection is limited. Because Culex mosquito vectors and avian malaria dynamics are strongly influenced by temperature and rainfall, future climate change is predicted to expand malaria infection to high-elevation forests and intensify malaria infection at lower elevations, likely resulting in future extinctions and loss of avian biodiversity in Hawaii. Novel, landscape-level mosquito control strategies are promising, but are logistically challenging and require costly long-term efforts. As an alternative or supplemental strategy, we evaluated the potential of releasing a gene-edited malaria-resistant honeycreeper (Iiwi, Drepanis coccinea) in Hawaiian rainforests; a strategy known as facilitated adaptation. While this approach also has significant technical challenges and costs, it may offer a more permanent solution to increasing malaria threats. If malaria-resistant honeycreepers can be developed, facilitated adaptation may provide a practical strategy for the reestablishment of abundant avian populations in Hawaiian forests. A successful strategy could be the release of malaria-resistant Iiwi in mid-elevation forests where development of a resistant population has the best chance of success. Establishment of a resistant Iiwi population could provide a source for dispersal and development of resistant populations in high-elevation forests and a permanent source of resistant individuals for translocation to other vulnerable areas.","language":"English","publisher":"Elsevier","doi":"10.1016/j.biocon.2019.108390","collaboration":"","usgsCitation":"Samuel, M., Liao, W., Atkinson, C.T., and Lapointe, D., 2019, Facilitated adaptation for conservation – Can gene editing save Hawaii's endangered birds from climate driven avian malaria?: Biological Conservation, v. 241, https://doi.org/10.1016/j.biocon.2019.108390.","productDescription":"108390, 9 p.","startPage":"108390","ipdsId":"IP-112465","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":458894,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.biocon.2019.108390","text":"Publisher Index Page"},{"id":437246,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9SAX5TR","text":"USGS data release","linkHelpText":"Hawaii Island, modelled density of malaria-resistant and -susceptible Iiwi following release of malaria-resistant birds under three climate change projections, 2030-2100"},{"id":374046,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -160.6201171875,\n              18.70869162255995\n            ],\n            [\n              -154.53369140625,\n              18.70869162255995\n            ],\n            [\n              -154.53369140625,\n              22.654571520098994\n            ],\n            [\n              -160.6201171875,\n              22.654571520098994\n            ],\n            [\n              -160.6201171875,\n              18.70869162255995\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"241","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Samuel, Michael D.","contributorId":206351,"corporation":false,"usgs":false,"family":"Samuel","given":"Michael D.","affiliations":[{"id":7122,"text":"University of Wisconsin","active":true,"usgs":false}],"preferred":false,"id":787250,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Liao, Wei","contributorId":147740,"corporation":false,"usgs":false,"family":"Liao","given":"Wei","email":"","affiliations":[{"id":13018,"text":"Department of Forest and Wildlife Ecology, University of Wisconsin, Madison","active":true,"usgs":false}],"preferred":false,"id":787251,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Atkinson, Carter T. 0000-0002-4232-5335 catkinson@usgs.gov","orcid":"https://orcid.org/0000-0002-4232-5335","contributorId":1124,"corporation":false,"usgs":true,"family":"Atkinson","given":"Carter","email":"catkinson@usgs.gov","middleInitial":"T.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true},{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true}],"preferred":true,"id":787252,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"LaPointe, Dennis A. 0000-0002-6323-263X dlapointe@usgs.gov","orcid":"https://orcid.org/0000-0002-6323-263X","contributorId":150365,"corporation":false,"usgs":true,"family":"LaPointe","given":"Dennis","email":"dlapointe@usgs.gov","middleInitial":"A.","affiliations":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"preferred":true,"id":787253,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70205563,"text":"cir1461 - 2019 - Flow modification in the Nation’s streams and rivers","interactions":[],"lastModifiedDate":"2022-04-19T20:34:04.630004","indexId":"cir1461","displayToPublicDate":"2019-12-24T15:32:57","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":307,"text":"Circular","code":"CIR","onlineIssn":"2330-5703","printIssn":"1067-084X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1461","displayTitle":"Flow Modification in the Nation's Streams and Rivers","title":"Flow modification in the Nation’s streams and rivers","docAbstract":"<p>This report summarizes a national assessment of flowing waters conducted by the U.S.&nbsp;Geological Survey’s (USGS) National Water-Quality Assessment (NAWQA) Project and addresses several pressing questions about the modification of natural flows in streams and rivers. The assessment is based on the integration, modeling, and synthesis of monitoring data collected by the USGS and the U.S.&nbsp;Environmental Protection Agency at more than 7,000&nbsp;streams and rivers across the conterminous United States from 1980 to 2014. Key findings include the following. First, flow in many of the Nation’s streams and rivers is different from what it would be under natural conditions. In particular, low flows are more frequent, are of shorter duration, and vary less from one year to the next than they would naturally. In addition, high flows have been reduced in magnitude, are of shorter duration, are less frequent, and vary less from one year to the next than they would naturally. Other characteristics of natural flows also have been modified. Second, over the last 60&nbsp;years (1955–2014), climatic trends have caused a change of 50&nbsp;percent or more in one or more streamflow attributes at two-thirds of climate-sensitive streamgaging sites. However, these climate-induced changes have been less influential on streamflow modification than have land and water-management practices. Third, in every region assessed, streamflow modification was associated with reduced ecological health, as indicated by two biological communities—invertebrates and fish. Biological communities were increasingly likely to be impaired (defined as having lost a statistically significant number of species) in streams with flows most different from natural conditions. Finally, several case studies are presented that illustrate viable management strategies for balancing the water needs of people and ecosystems.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/cir1461","collaboration":"National Water-Quality Program<br/>National Water-Quality Assessment Project","usgsCitation":"Carlisle, D.M., Wolock, D.M., Konrad, C.P., McCabe, G.J., Eng, K., Grantham, T.E., and Mahler, B., 2019, Flow modification in the Nation’s streams and rivers: U.S. Geological Survey Circular 1461, 75 p., https://doi.org/10.3133/cir1461.","productDescription":"ix, 75 p.","numberOfPages":"90","onlineOnly":"N","ipdsId":"IP-103600","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":437247,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9R4FFGG","text":"USGS data release","linkHelpText":"Predicted Streamflow Modification in Contiguous United States Streams"},{"id":399129,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109567.htm"},{"id":370324,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/circ/1461/cir1461.pdf","text":"Report","linkFileType":{"id":1,"text":"pdf"},"description":"Circular 1461"},{"id":370323,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/circ/1461/coverthb2.jpg"}],"country":"United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -125.41992187499999,\n              47.87214396888731\n            ],\n            [\n              -125.33203125,\n              43.70759350405294\n            ],\n            [\n              -124.45312499999999,\n              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45.767522962149876\n            ],\n            [\n              -88.76953125,\n              48.516604348867475\n            ],\n            [\n              -95.625,\n              49.15296965617042\n            ],\n            [\n              -114.08203125,\n              49.15296965617042\n            ],\n            [\n              -123.22265625000001,\n              49.439556958940855\n            ],\n            [\n              -125.41992187499999,\n              47.87214396888731\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"https://water.usgs.gov/nawqa/\" target=\"blank\" data-mce-href=\"https://water.usgs.gov/nawqa/\">National Water-Quality Program</a><br>U.S. Geological Survey<br>413 National Center<br>12201 Sunrise Valley Drive<br>Reston, VA 20192</p>","tableOfContents":"<ul><li>Foreword</li><li>Acknowledgments</li><li>Chapter A. Overview</li><li>Chapter B. National Assessment of Streamflow Modification</li><li>Chapter C. Streamflow Modification Associated with Land and Water Management</li><li>Chapter D. Streamflow Modification and Climate</li><li>Chapter E. Ecological Consequences of Streamflow Modification</li><li>Chapter F. Managing Modified Streamflows</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2019-12-24","noUsgsAuthors":false,"publicationDate":"2019-12-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Carlisle, Daren M. 0000-0002-7367-348X dcarlisle@usgs.gov","orcid":"https://orcid.org/0000-0002-7367-348X","contributorId":513,"corporation":false,"usgs":true,"family":"Carlisle","given":"Daren","email":"dcarlisle@usgs.gov","middleInitial":"M.","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":771664,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wolock, David M. 0000-0002-6209-938X","orcid":"https://orcid.org/0000-0002-6209-938X","contributorId":219213,"corporation":false,"usgs":true,"family":"Wolock","given":"David","email":"","middleInitial":"M.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":771665,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Konrad, Christopher P. 0000-0002-7354-547X","orcid":"https://orcid.org/0000-0002-7354-547X","contributorId":217885,"corporation":false,"usgs":true,"family":"Konrad","given":"Christopher P.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":771666,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McCabe, Gregory J. 0000-0002-9258-2997 gmccabe@usgs.gov","orcid":"https://orcid.org/0000-0002-9258-2997","contributorId":200854,"corporation":false,"usgs":true,"family":"McCabe","given":"Gregory","email":"gmccabe@usgs.gov","middleInitial":"J.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":771667,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Eng, Ken 0000-0001-6838-5849 keng@usgs.gov","orcid":"https://orcid.org/0000-0001-6838-5849","contributorId":3580,"corporation":false,"usgs":true,"family":"Eng","given":"Ken","email":"keng@usgs.gov","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":771668,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Grantham, Theodore E. tgrantham@usgs.gov","contributorId":219214,"corporation":false,"usgs":false,"family":"Grantham","given":"Theodore","email":"tgrantham@usgs.gov","middleInitial":"E.","affiliations":[{"id":33770,"text":"University of California at Berkeley","active":true,"usgs":false}],"preferred":false,"id":771669,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"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":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":771670,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70215931,"text":"70215931 - 2019 - Primarily resident grizzly bears respond to late-season elk harvest","interactions":[],"lastModifiedDate":"2020-11-02T12:37:43.841033","indexId":"70215931","displayToPublicDate":"2019-12-24T06:33:00","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3671,"text":"Ursus","active":true,"publicationSubtype":{"id":10}},"title":"Primarily resident grizzly bears respond to late-season elk harvest","docAbstract":"<p><span>Autumn ungulate hunting in the Greater Yellowstone Ecosystem carries the risk of hunter–grizzly bear (</span><i>Ursus arctos</i><span>) conflict and creates a substantial challenge for managers. For Grand Teton National Park, Wyoming, USA, a key information need is whether increased availability of elk (</span><i>Cervus canadensis</i><span>) carcasses during a late autumn (Nov–Dec) harvest within the national park attracts grizzly bears and increases the potential for conflict with hunters. Using a robust design analysis with 6 primary sampling periods during 2014–2015, we tested the hypothesis that the elk harvest resulted in temporary movements of grizzly bears into the hunt areas, thus increasing bear numbers. We detected 31 unique individuals (6 F, 25 M) through genetic sampling and retained 26 encounter histories for analysis. Markovian movement models had more support than a null model of no temporary movement. Contrary to our research hypothesis, temporary movements into the study area occurred between the July–August (no hunt;&nbsp;</span><i>N̄</i><sub>2014–2015</sub><span>&nbsp;= 5) and September–October (no hunt;&nbsp;</span><i>N̄</i><sub>2014–2015</sub><span>&nbsp;= 24) primary periods each year, rather than during the transition from September–October (no hunt) to November–December (hunt;&nbsp;</span><i>N̄</i><sub>2014–2015</sub><span>&nbsp;= 15). A post hoc analysis indicated that September–October population estimates were biased high by detections of transient bears. Grizzly bear presence during the elk hunt was limited to approximately 15 resident bears that specialized in accessing elk carcasses. The late timing of the elk hunt likely moderated the effect of carcasses as a food attractant because it coincides with the onset of hibernation. From a population response perspective, the current timing of the elk harvest likely represents a scenario of low relative risk of hunter–bear conflicts. The risk of hunter–grizzly bear encounters remains, but may be more a function of factors that operate at the level of individual bears and hunters, such as hunter movements and bear responses to olfactory cues.</span></p>","language":"English","publisher":"International Association for Bear Research and Management","doi":"10.2192/URSUS-D-18-00018R2","usgsCitation":"van Manen, F.T., Ebinger, M.R., Gustine, D.D., Haroldson, M.A., Wilmot, K.R., and Whitman, C., 2019, Primarily resident grizzly bears respond to late-season elk harvest: Ursus, v. 30, no. e1, 15 p., https://doi.org/10.2192/URSUS-D-18-00018R2.","productDescription":"15 p.","ipdsId":"IP-099097","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":458896,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.2192/ursus-d-18-00018r2","text":"Publisher Index Page"},{"id":437249,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9IWSJUX","text":"USGS data release","linkHelpText":"Detection histories of grizzly bears in Grand Teton National Park, 2014-2015"},{"id":380007,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","otherGeospatial":"Grand Teton National Park","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -110.85205078124999,\n              43.6599240747891\n            ],\n            [\n              -110.49224853515625,\n              43.6599240747891\n            ],\n            [\n              -110.49224853515625,\n              43.91372326852401\n            ],\n            [\n              -110.85205078124999,\n              43.91372326852401\n            ],\n            [\n              -110.85205078124999,\n              43.6599240747891\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"30","issue":"e1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"van Manen, Frank T. 0000-0001-5340-8489 fvanmanen@usgs.gov","orcid":"https://orcid.org/0000-0001-5340-8489","contributorId":2267,"corporation":false,"usgs":true,"family":"van Manen","given":"Frank","email":"fvanmanen@usgs.gov","middleInitial":"T.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":803625,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ebinger, Michael R. 0000-0002-2586-7829 mebinger@usgs.gov","orcid":"https://orcid.org/0000-0002-2586-7829","contributorId":244264,"corporation":false,"usgs":true,"family":"Ebinger","given":"Michael","email":"mebinger@usgs.gov","middleInitial":"R.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":803626,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gustine, David D. 0000-0003-1087-1937","orcid":"https://orcid.org/0000-0003-1087-1937","contributorId":201734,"corporation":false,"usgs":false,"family":"Gustine","given":"David","email":"","middleInitial":"D.","affiliations":[{"id":36245,"text":"NPS","active":true,"usgs":false}],"preferred":false,"id":803627,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Haroldson, Mark A. 0000-0002-7457-7676 mharoldson@usgs.gov","orcid":"https://orcid.org/0000-0002-7457-7676","contributorId":1773,"corporation":false,"usgs":true,"family":"Haroldson","given":"Mark","email":"mharoldson@usgs.gov","middleInitial":"A.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":803628,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wilmot, Katharine R.","contributorId":244265,"corporation":false,"usgs":false,"family":"Wilmot","given":"Katharine","email":"","middleInitial":"R.","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":803629,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Whitman, Craig 0000-0002-1187-4649 cwhitman@usgs.gov","orcid":"https://orcid.org/0000-0002-1187-4649","contributorId":206044,"corporation":false,"usgs":true,"family":"Whitman","given":"Craig","email":"cwhitman@usgs.gov","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":803630,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70205417,"text":"sir20195099 - 2019 - Flood-inundation maps for the North Platte River at Scottsbluff and Gering, Nebraska, 2018","interactions":[],"lastModifiedDate":"2022-04-22T21:43:56.878264","indexId":"sir20195099","displayToPublicDate":"2019-12-23T20:34:51","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2019-5099","displayTitle":"Flood-Inundation Maps for the North Platte River at Scottsbluff and Gering, Nebraska, 2018","title":"Flood-inundation maps for the North Platte River at Scottsbluff and Gering, Nebraska, 2018","docAbstract":"<p>Digital flood-inundation maps for an 8.8-mile reach of the North Platte River, from 1.5 miles upstream from the Highway 92 bridge to 3 miles downstream from the Highway 71 bridge in Scottsbluff County, were created by the U.S. Geological Survey (USGS) in cooperation with the Cities of Scottsbluff and Gering, Nebraska. The flood-inundation maps, which can be accessed through the Flood Inundation Mapping (FIM) Program website at <a data-mce-href=\"https://www.usgs.gov/mission-areas/water-resources/science/flood-inundation-mapping-fim-program?qt-science_center_objects=0#qt-science_center_objects\" href=\"https://www.usgs.gov/mission-areas/water-resources/science/flood-inundation-mapping-fim-program?qt-science_center_objects=0#qt-science_center_objects\">https://www.usgs.gov/mission-areas/water-resources/science/flood-inundation-mapping-fim-program?qt-science_center_objects=0#qt-science_center_objects</a>, depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at the USGS streamgage on the North Platte River at Scottsbluff, Nebr. (station number 06680500). Near-real-time stages at this streamgage may be obtained on the internet from the USGS National Water Information System at <a data-mce-href=\"https://doi.org/10.5066/F7P55KJN\" href=\"https://doi.org/10.5066/F7P55KJN\">https://doi.org/10.5066/F7P55KJN</a> or from the National Weather Service Advanced Hydrologic Prediction Service (site SBRN1) at <a data-mce-href=\"https://water.weather.gov/ahps2/hydrograph.php?wfo=cys&amp;gage=sbrn1\" href=\"https://water.weather.gov/ahps2/hydrograph.php?wfo=cys&amp;gage=sbrn1\">https://water.weather.gov/ahps2/hydrograph.php?wfo=cys&amp;gage=sbrn1</a>.</p><p>Flood profiles were computed for the stream reach by means of a one-dimensional step-backwater model. The model was calibrated by using the current (2018) stage-discharge relation at the North Platte River at Scottsbluff, Nebr., streamgage.</p><p>The hydraulic model was then used to compute 10 water-surface profiles for flood stages at 1-foot (ft) intervals referenced to the streamgage datum and ranging from 9 ft, or near bankfull, to 18 ft, which exceeds the stage that corresponds to the estimated 1-percent annual exceedance probability flood (100-year recurrence interval flood). The simulated water-surface profiles were then combined with a geographic information system digital elevation model derived from light detection and ranging data having a 0.6-ft root mean square error and 2-ft horizontal resolution resampled to a 6-ft grid to delineate the area flooded at each water level. The availability of these maps, along with internet information regarding current stage from the USGS streamgage, may provide emergency management personnel and residents with information that is critical for flood response activities such as evacuations and road closures, as well as for postflood recovery efforts.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195099","collaboration":"Prepared in cooperation with the City of Scottsbluff and the City of Gering","usgsCitation":"Strauch, K.R., 2019, Flood-inundation maps for the North Platte River at Scottsbluff and Gering, Nebraska, 2018: U.S. Geological Survey Scientific Investigations Report 2019–5099, 9 p., https://doi.org/10.3133/sir20195099.","productDescription":"Report: vi, 9 p.; Data Release","numberOfPages":"20","onlineOnly":"Y","ipdsId":"IP-102434","costCenters":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"links":[{"id":399544,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109564.htm"},{"id":370451,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5099/sir20195099.pdf","text":"Report","size":"25.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019–5099"},{"id":370452,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9NCAIKN","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Flood-inundation geospatial datasets for the North Platte River at Scottsbluff and Gering, Nebraska"},{"id":370450,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5099/coverthb.jpg"}],"country":"United States","state":"Nebraska","city":"Scottsbluff, Gering","otherGeospatial":"North Platte River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -104.05426025390625,\n              41.74467659677642\n            ],\n            [\n              -103.33740234375,\n              41.74467659677642\n            ],\n            [\n              -103.33740234375,\n              42.05948945192712\n            ],\n            [\n              -104.05426025390625,\n              42.05948945192712\n            ],\n            [\n              -104.05426025390625,\n              41.74467659677642\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p>Director,&nbsp;<a data-mce-href=\"https://www.usgs.gov/centers/ne-water\" href=\"https://www.usgs.gov/centers/ne-water\">Nebraska Water Science Center</a> <br>U.S. Geological Survey<br>5231 South 19th Street <br>Lincoln, NE 68512</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Creation of Flood-Inundation-Map Library</li><li>Summary</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2019-12-23","noUsgsAuthors":false,"publicationDate":"2019-12-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Strauch, Kellan R. 0000-0002-7218-2099","orcid":"https://orcid.org/0000-0002-7218-2099","contributorId":208562,"corporation":false,"usgs":true,"family":"Strauch","given":"Kellan R.","affiliations":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"preferred":true,"id":771101,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70207321,"text":"sim3445 - 2019 - Bathymetric map and surface area and capacity table for Beaver Lake near Rogers, Arkansas, 2018","interactions":[],"lastModifiedDate":"2022-04-22T19:51:18.99807","indexId":"sim3445","displayToPublicDate":"2019-12-23T20:20:39","publicationYear":"2019","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":"3445","displayTitle":"Bathymetric Map and Surface Area and Capacity Table for Beaver Lake near Rogers, Arkansas, 2018","title":"Bathymetric map and surface area and capacity table for Beaver Lake near Rogers, Arkansas, 2018","docAbstract":"<p>Beaver Lake was constructed in 1966 on the White River in the northwest corner of Arkansas for flood control, hydroelectric power, public water supply, and recreation. The surface area of Beaver Lake is about 27,900 acres and approximately 449 miles of shoreline are at the conservation pool level (1,120 feet above the North American Vertical Datum of 1988). Sedimentation in reservoirs can result in reduced water storage capacity and a reduction in usable aquatic habitat. Therefore, accurate and up-to-date estimates of reservoir water capacity are important for managing pool levels, power generation, recreation, and downstream aquatic habitat. Many of the lakes operated by the U.S. Army Corps of Engineers are periodically surveyed to monitor bathymetric changes that affect water capacity. In October 2018, the U.S. Geological Survey, in cooperation with the U.S. Army Corps of Engineers, completed one such survey of Beaver Lake using a multibeam echosounder. The echosounder data were combined with light detection and ranging (lidar) data to prepare a bathymetric map and a surface area and capacity table.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3445","collaboration":"Prepared in cooperation with the U.S. Army Corp of Engineers, Southwestern Division, Little Rock District","usgsCitation":"Huizinga, R.J., Ellis, J.T., Sharpe, J.B., LeRoy, J.Z., and Richards, J.M., 2019, Bathymetric map and surface area and capacity table for Beaver Lake near Rogers, Arkansas, 2018: U.S. Geological Survey Scientific Investigations Map 3445,\n2 sheets, https://doi.org/10.3133/sim3445.","productDescription":"2 Sheets: 44 x 36 inches; Data Release","onlineOnly":"Y","ipdsId":"IP-113370","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":370609,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3445/coverthb.jpg"},{"id":399518,"rank":5,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109565.htm"},{"id":370612,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P91PLLGV","text":"USGS data release","linkHelpText":"Bathymetric and supporting data for Beaver Lake near Rogers, Arkansas, 2018"},{"id":370610,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3445/sim3445_sheet1.pdf","text":"Sheet 1","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3445 Sheet 1"},{"id":370611,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3445/sim3445_sheet2.pdf","text":"Sheet 2","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3445 Sheet 2"}],"scale":"24000","country":"United States","state":"Arkansas","city":"Rogers","otherGeospatial":"Beaver Lake","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -94.11575317382812,\n              36.17446549576358\n            ],\n            [\n              -93.79440307617188,\n              36.17446549576358\n            ],\n            [\n              -93.79440307617188,\n              36.45829281489\n            ],\n            [\n              -94.11575317382812,\n              36.45829281489\n            ],\n            [\n              -94.11575317382812,\n              36.17446549576358\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p>Director, <a data-mce-href=\"https://www.usgs.gov/centers/cm-water\" href=\"https://www.usgs.gov/centers/cm-water\">Central Midwest Water Science Center</a><br>U.S. Geological Survey <br>1400 Independence Road<br>Rolla, MO 65401</p>","tableOfContents":"<ul><li>Introduction</li><li>Methods</li><li>Bathymetric Data Collection Quality Assurance</li><li>Bathymetric Surface and Contour Quality Assurance</li><li>Bathymetry and Surface Area and Capacity</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2019-12-23","noUsgsAuthors":false,"publicationDate":"2019-12-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Huizinga, Richard J. 0000-0002-2940-2324 huizinga@usgs.gov","orcid":"https://orcid.org/0000-0002-2940-2324","contributorId":2089,"corporation":false,"usgs":true,"family":"Huizinga","given":"Richard","email":"huizinga@usgs.gov","middleInitial":"J.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":777701,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ellis, Jarrett T. 0000-0001-9928-1030","orcid":"https://orcid.org/0000-0001-9928-1030","contributorId":210378,"corporation":false,"usgs":true,"family":"Ellis","given":"Jarrett","email":"","middleInitial":"T.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":777700,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sharpe, Jennifer B. 0000-0002-5192-7848 jbsharpe@usgs.gov","orcid":"https://orcid.org/0000-0002-5192-7848","contributorId":2825,"corporation":false,"usgs":true,"family":"Sharpe","given":"Jennifer","email":"jbsharpe@usgs.gov","middleInitial":"B.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":777703,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"LeRoy, Jessica Z. 0000-0003-4035-6872 jzinger@usgs.gov","orcid":"https://orcid.org/0000-0003-4035-6872","contributorId":174534,"corporation":false,"usgs":true,"family":"LeRoy","given":"Jessica","email":"jzinger@usgs.gov","middleInitial":"Z.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true},{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true},{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true}],"preferred":true,"id":777699,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Richards, Joseph M. 0000-0002-9822-2706","orcid":"https://orcid.org/0000-0002-9822-2706","contributorId":202877,"corporation":false,"usgs":true,"family":"Richards","given":"Joseph M.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":777702,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70208589,"text":"70208589 - 2019 - Temporal variations in scrubbing of magmatic gases at the summit of Kīlauea Volcano, Hawai‘i","interactions":[],"lastModifiedDate":"2020-02-19T20:22:54","indexId":"70208589","displayToPublicDate":"2019-12-23T20:19:17","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Temporal variations in scrubbing of magmatic gases at the summit of Kīlauea Volcano, Hawai‘i","docAbstract":"Measurements of gas compositions and emission rates play a major role in monitoring restless volcanoes. However, thermodynamic calculations imply that scrubbing by groundwater will prevent most HCl and significant SO2 emissions until dry pathways are established, thus leading to underestimates of gas released from magma and magma volumes. Despite the significance, direct evidence for scrubbing is mostly lacking. Based on 50 water samples collected between 2003 and 2011 from the deep NSF Well at the summit of Kīlauea Volcano we show that the chemical and stable isotope compositions of groundwater were modified by magmatic gas condensation. Temporal variations of dissolved SO42- and Cl- in the water coincided with changes in magmatic and volcanic activity. In 2006 up to ~40% of the SO2 and HCl degassed from magma may have been scrubbed by groundwater.","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2019GL085904","usgsCitation":"Hurwitz, S., and Anderson, K.R., 2019, Temporal variations in scrubbing of magmatic gases at the summit of Kīlauea Volcano, Hawai‘i: Geophysical Research Letters, v. 46, no. 24, p. 14469-14476, https://doi.org/10.1029/2019GL085904.","productDescription":"8 p.","startPage":"14469","endPage":"14476","ipdsId":"IP-113719","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":372433,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Kīlauea Volcano","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -155.30118942260742,\n              19.390019824987313\n            ],\n            [\n              -155.23475646972656,\n              19.390019824987313\n            ],\n            [\n              -155.23475646972656,\n              19.43907564961802\n            ],\n            [\n              -155.30118942260742,\n              19.43907564961802\n            ],\n            [\n              -155.30118942260742,\n              19.390019824987313\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"46","issue":"24","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2019-12-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Hurwitz, Shaul 0000-0001-5142-6886 shaulh@usgs.gov","orcid":"https://orcid.org/0000-0001-5142-6886","contributorId":2169,"corporation":false,"usgs":true,"family":"Hurwitz","given":"Shaul","email":"shaulh@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":782630,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Anderson, Kyle R. 0000-0001-8041-3996 kranderson@usgs.gov","orcid":"https://orcid.org/0000-0001-8041-3996","contributorId":3522,"corporation":false,"usgs":true,"family":"Anderson","given":"Kyle","email":"kranderson@usgs.gov","middleInitial":"R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":782631,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70207260,"text":"sir20195143 - 2019 - Methods for estimating the magnitude and frequency of peak streamflows for unregulated streams in Oklahoma developed by using streamflow data through 2017","interactions":[],"lastModifiedDate":"2022-04-25T20:22:15.899417","indexId":"sir20195143","displayToPublicDate":"2019-12-23T18:33:30","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2019-5143","displayTitle":"Methods for Estimating the Magnitude and Frequency of Peak Streamflows for Unregulated Streams in Oklahoma Developed by Using Streamflow Data Through 2017","title":"Methods for estimating the magnitude and frequency of peak streamflows for unregulated streams in Oklahoma developed by using streamflow data through 2017","docAbstract":"<p>The U.S. Geological Survey (USGS), in cooperation with the Oklahoma Department of Transportation, updated peak-streamflow regression equations for estimating flows with annual exceedance probabilities from 50 to 0.2 percent for the State of Oklahoma. These regression equations incorporate basin characteristics to estimate peak-streamflow magnitude and frequency throughout the State by use of a generalized least-squares regression analysis. The most statistically significant independent variables required to estimate peak-streamflow magnitude and frequency for unregulated streams in Oklahoma are contributing drainage area, mean-annual precipitation, and main-channel slope. The regression equations are applicable for stream basins with drainage areas less than 2,510 square miles that are not affected by regulation. The standard model error ranged from 31.28 to 49.32 percent for the different annual exceedance probabilities that were computed.</p><p>Annual-maximum peak flows observed at 212 USGS streamgages through water year 2017 were used for the regression analysis, excluding the Oklahoma Panhandle region. The USGS StreamStats web application was used to obtain the independent variables required for the peak-streamflow regression equations. Limitations on the use of the regression equations and the reliability of regression estimates for natural unregulated streams are described. Log-Pearson Type III analysis information, basin and climate characteristics, and the peak-streamflow frequency estimates for the 212 streamgages in and near Oklahoma are provided in this report.</p><p>This report contains descriptions of the methods that can be used to estimate peak streamflows at ungaged sites by using estimates from streamgages on unregulated streams. For ungaged sites on urban streams and streams regulated by small floodwater-retarding structures, an adjustment of the statewide regression equations for natural unregulated streams can be used to estimate peak-streamflow magnitude and frequency.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195143","collaboration":"Prepared in cooperation with the Oklahoma Department of Transportation","usgsCitation":"Lewis, J.M., Hunter, S.L., and Labriola, L.G., 2019, Methods for estimating the magnitude and frequency of peak streamflows for unregulated streams in Oklahoma developed by using streamflow data through 2017 (ver. 1.1, March 2020): U.S. Geological Survey Scientific Investigations Report 2019–5143, 39 p., https://doi.org/10.3133/sir20195143.","productDescription":"Report: v, 39 p.; Data Release","numberOfPages":"50","onlineOnly":"Y","ipdsId":"IP-111975","costCenters":[{"id":516,"text":"Oklahoma Water Science Center","active":true,"usgs":true}],"links":[{"id":373219,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5143/sir20195143_v1.1.pdf","text":"Report","size":"5.22 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019–5143"},{"id":370619,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9B99TQZ","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Data release of basin characteristics, generalized skew map and peak-streamflow frequency estimates in Oklahoma, 2017"},{"id":373218,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5143/coverthb2.jpg"},{"id":373266,"rank":4,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2019/5143/versionHist.txt","text":"Version History","description":"Version History"},{"id":399618,"rank":5,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109563.htm"}],"country":"United States","state":"Arkansas, Kansas, Missouri, Oklahoma, Texas","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -102.919921875,\n              36.87962060502676\n            ],\n            [\n              -102.83203125,\n              34.415973384481866\n            ],\n            [\n              -97.91015624999999,\n              33.97980872872457\n            ],\n            [\n              -94.5703125,\n              33.17434155100208\n            ],\n            [\n              -93.515625,\n              33.97980872872457\n            ],\n            [\n              -93.251953125,\n              37.125286284966805\n            ],\n            [\n              -93.7353515625,\n              38.09998264736481\n            ],\n            [\n              -99.8876953125,\n              38.09998264736481\n            ],\n            [\n              -101.953125,\n              37.71859032558816\n            ],\n            [\n              -102.919921875,\n              36.87962060502676\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","edition":"Version 1.1: March 2020; Version 1.0: December 2019","contact":"<p>Director,&nbsp;<a data-mce-href=\"https://www.usgs.gov/centers/tx-water/\" href=\"https://www.usgs.gov/centers/tx-water/\">Oklahoma-Texas Water Science Center</a><br>U.S. Geological Survey<br>1505 Ferguson Lane<br>Austin, Texas 78754–4501<br></p>","tableOfContents":"<ul><li>Abstract</li><li>Introduction</li><li>Data Development</li><li>Estimates of Magnitude and Frequency of Peak Streamflows at Streamgages on Unregulated Streams</li><li>Estimates of Magnitude and Frequency of Peak Streamflows at Ungaged Sites on Unregulated Streams</li><li>Application of Methods</li><li>Summary</li><li>Acknowledgments</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"publishedDate":"2019-12-23","revisedDate":"2020-03-17","noUsgsAuthors":false,"publicationDate":"2019-12-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Lewis, Jason M. 0000-0001-5337-1890 jmlewis@usgs.gov","orcid":"https://orcid.org/0000-0001-5337-1890","contributorId":3854,"corporation":false,"usgs":true,"family":"Lewis","given":"Jason","email":"jmlewis@usgs.gov","middleInitial":"M.","affiliations":[{"id":516,"text":"Oklahoma Water Science Center","active":true,"usgs":true}],"preferred":true,"id":777485,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hunter, Shelby L. 0000-0002-3049-7498 slhunter@usgs.gov","orcid":"https://orcid.org/0000-0002-3049-7498","contributorId":196727,"corporation":false,"usgs":true,"family":"Hunter","given":"Shelby","email":"slhunter@usgs.gov","middleInitial":"L.","affiliations":[{"id":516,"text":"Oklahoma Water Science Center","active":true,"usgs":true}],"preferred":true,"id":777486,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Labriola, L.G. 0000-0002-5096-2940","orcid":"https://orcid.org/0000-0002-5096-2940","contributorId":216625,"corporation":false,"usgs":true,"family":"Labriola","given":"L.G.","email":"","affiliations":[{"id":516,"text":"Oklahoma Water Science Center","active":true,"usgs":true}],"preferred":true,"id":777487,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70206599,"text":"sir20195132 - 2019 - A hydrogeomorphic classification of connectivity of large rivers of the Upper Midwest, United States","interactions":[],"lastModifiedDate":"2022-04-25T19:36:10.908694","indexId":"sir20195132","displayToPublicDate":"2019-12-23T18:29:22","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2019-5132","displayTitle":"A Hydrogeomorphic Classification of Connectivity of Large Rivers of the Upper Midwest, United States","title":"A hydrogeomorphic classification of connectivity of large rivers of the Upper Midwest, United States","docAbstract":"<p>River connectivity is defined as the water-mediated exchange of matter, energy, and biota between different elements of the riverine landscape. Connectivity is an especially important concept in large-river corridors (channel plus floodplain ) because large rivers integrate fluxes of water, sediment, nutrients, contaminants, and other transported constituents emanating from large contributing drainage basins, and thereby contribute to the complexity of large-river ecosystems. Large rivers are also highly valued for socioeconomic goods and services, which has led to historical fragmentation, lack of connectivity, and contentiousness about best policies for managing large-river corridors. The classification is intended to serve as a template for understanding geographic variation in large rivers within the Midwest, to aid in designing scientific studies of large river ecological processes, and to match specific river-management and restoration objectives to specific river reaches. The focus of the classification is on measuring river connectivity from available hydrological and geomorphic data.</p><p>We provide a multiscale assessment and classification for segments of 15 rivers that meet various criteria for largeness. All rivers are tributaries to the Mississippi River system. The 11,600 kilometers (km) that qualified as large were classified by major alterations (unimpounded, navigation pools, storage reservoir) and additionally assessed for their network continuity as a function of numbers and heights of dams. Among the 15 rivers, 55 percent of segment length was unimpounded, 30 percent was in navigation pools, and 15 percent was under storage reservoirs. Assessment of network longitudinal connectivity among river segments documented the contrast between river segments with low-head navigation dams (Upper Mississippi, Illinois, Ohio, Green, and Cumberland Rivers) and those segments with high-head dams (mostly in the Upper Missouri River). The longest unimpounded river pathways exist in the Lower Missouri River and connected tributaries where nearly 1,300 km of the Missouri River connect to an additional 1,800 km of the Middle and Lower Mississippi Rivers.</p><p>At our finest scale, we present a statistically based, component classification based on 10-km segments. Cluster analysis of hydrologic variables from 66 streamflow-gaging stations yielded 5 clusters calculated from 5 ecohydrological metrics related to lateral connectivity with the floodplain. A separate cluster analysis of 5 geomorphologic variables associated with each of the 1,172 river segments also yielded 5 clusters. When the hydrologic variables were associated with corresponding segments, the cluster analysis yielded 8 hydrogeomorphic clusters that could be explained in terms of their contribution to floodplain connectivity. Although the clusters overlap considerably in principal component space, the resulting hydrogeomorphic classification leads to a physically reasonable distribution of classes. The resulting classification is intended to increase geographic awareness of the range of variation of connectivity potential among large rivers of the Upper Midwest, to increase understanding of the extent of alteration of these rivers, and potentially to serve as a template for stratifying study designs of large-river corridor ecological processes.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195132","usgsCitation":"Jacobson, R.B., Rohweder, J.J., and DeJager, N.R., 2019, A hydrogeomorphic classification of connectivity of large rivers of the Upper Midwest, United States: U.S. Geological Survey Scientific Investigations Report 2019–5132, 55 p., https://doi.org/10.3133/sir20195132.","productDescription":"Report: vi, 55 p.; 2 Data Releases","numberOfPages":"66","onlineOnly":"Y","ipdsId":"IP-104678","costCenters":[{"id":192,"text":"Columbia Environmental Research 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States"},{"id":370622,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5132/coverthb.jpg"}],"country":"United States","state":"Colorado, Illinois, Indiana, Iowa, Kansas, Kentucky, Minnesota, Missouri, Montana, Nebraska, New York, North Carolilna,North Dakota, Ohio, Pennsylvania, South Dakota, Tennessee, Virginia, West Virginia, Wisconsin, Wyoming","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -85.8251953125,\n              35.460669951495305\n            ],\n            [\n              -80.5078125,\n              37.020098201368114\n            ],\n            [\n              -80.15625,\n              35.60371874069731\n            ],\n            [\n              -79.541015625,\n              37.43997405227057\n            ],\n     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Cited</li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2019-12-23","noUsgsAuthors":false,"publicationDate":"2019-12-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Jacobson, Robert B. 0000-0002-8368-2064 rjacobson@usgs.gov","orcid":"https://orcid.org/0000-0002-8368-2064","contributorId":1289,"corporation":false,"usgs":true,"family":"Jacobson","given":"Robert","email":"rjacobson@usgs.gov","middleInitial":"B.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":775104,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rohweder, Jason J. 0000-0001-5131-9773 jrohweder@usgs.gov","orcid":"https://orcid.org/0000-0001-5131-9773","contributorId":150539,"corporation":false,"usgs":true,"family":"Rohweder","given":"Jason","email":"jrohweder@usgs.gov","middleInitial":"J.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":775105,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"De Jager, Nathan R. 0000-0002-6649-4125 ndejager@usgs.gov","orcid":"https://orcid.org/0000-0002-6649-4125","contributorId":3717,"corporation":false,"usgs":true,"family":"De Jager","given":"Nathan","email":"ndejager@usgs.gov","middleInitial":"R.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":775106,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
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