{"pageNumber":"111","pageRowStart":"2750","pageSize":"25","recordCount":40783,"records":[{"id":70247940,"text":"70247940 - 2023 - Confirmation of significant sea turtle nesting activity on a remote island chain in the Gulf of Mexico","interactions":[],"lastModifiedDate":"2023-08-25T14:14:08.823257","indexId":"70247940","displayToPublicDate":"2023-08-25T09:03:51","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Confirmation of significant sea turtle nesting activity on a remote island chain in the Gulf of Mexico","docAbstract":"Globally, six of the seven sea turtle species are threatened or endangered and as such, monitoring reproductive activity for these species is necessary for effective population recovery. Remote beaches provide a challenge to conducting these surveys, which often results in data gaps that can hamper management planning. Throughout the summer of 2022, aerial surveys were conducted over the Chandeleur Islands in the Gulf of Mexico. Turtle crawls were photographed for subsequent review by 10 expert observers. Whenever possible, ground surveys were conducted, and samples of unhatched eggs or dead hatchlings were collected. A summary of historic reports of sea turtle nesting activity at this site was also compiled. On 11 days between May 4, 2022, and July 30, 2022, photographs of 55 potential sea turtle crawls were taken. Observers identified 54 of those as being made by a sea turtle. There was high-to-moderate certainty that 16 of those crawls were nests, that 14 were made by loggerheads, and that two were made by Kemp's ridleys. Observers were least certain of species identification when surveys were conducted during rainy weather. Genetic analyses based on mitochondrial and nuclear DNA were conducted on samples from five nests and those analyses confirmed that three nests were laid by Kemp's ridleys and two were laid by loggerheads. Historic records from the Chandeleur Islands substantiate claims that the Chandeleurs have supported sea turtle nesting activity for decades; however, the consistency of this activity remains unknown. Our aerial surveys, particularly when coupled with imaging, were a useful tool for documenting nesting activity on these remote islands. Future monitoring programs at this site could benefit from a standardized aerial survey program with a seaplane so trends in nesting activity could be determined particularly as the beach undergoes restoration.","language":"English","publisher":"John Wiley & Sons, Inc.","doi":"10.1002/ece3.10448","usgsCitation":"Lamont, M., Ingram, D., Baker, T., Weigel, M., and Shamblin, B.M., 2023, Confirmation of significant sea turtle nesting activity on a remote island chain in the Gulf of Mexico: Ecology and Evolution, v. 13, no. 8, e10448, 10 p., https://doi.org/10.1002/ece3.10448.","productDescription":"e10448, 10 p.","ipdsId":"IP-152524","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":442305,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.10448","text":"Publisher Index 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Todd","contributorId":289809,"corporation":false,"usgs":false,"family":"Baker","given":"Todd","email":"","affiliations":[{"id":62256,"text":"LDWF","active":true,"usgs":false}],"preferred":false,"id":881146,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Weigel, Matt","contributorId":328735,"corporation":false,"usgs":false,"family":"Weigel","given":"Matt","email":"","affiliations":[{"id":12717,"text":"Louisiana Department of Wildlife and Fisheries","active":true,"usgs":false}],"preferred":false,"id":881147,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Shamblin, Brian M.","contributorId":138897,"corporation":false,"usgs":false,"family":"Shamblin","given":"Brian","email":"","middleInitial":"M.","affiliations":[{"id":12573,"text":"Daniel B. Warnell School of Forestry and Natural Resource, Athens Georiga","active":true,"usgs":false}],"preferred":false,"id":881148,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70247961,"text":"70247961 - 2023 - Identifying drivers of population dynamics for a stream breeding amphibian using time series of egg mass counts","interactions":[],"lastModifiedDate":"2023-08-29T13:49:07.077807","indexId":"70247961","displayToPublicDate":"2023-08-24T08:39:19","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Identifying drivers of population dynamics for a stream breeding amphibian using time series of egg mass counts","docAbstract":"<p><span>The decline in amphibian populations is one of the starkest examples of the biodiversity crisis. For stream breeding amphibians, alterations to natural flow regimes by dams, water diversions, and climate change have been implicated in declines and extirpations. Identifying drivers of amphibian declines requires long time series of abundance data because amphibian populations can exhibit high natural variability. Multiple population viability analysis (MPVA) models integrate abundance data and share information from different populations to estimate how environmental factors influence population growth. Flow alteration has been linked to declines and extirpations in the Foothill Yellow-legged Frog (</span><i>Rana boylii</i><span>), a stream breeding amphibian native to California and Oregon. To date, no study has jointly analyzed abundance data from populations throughout the range of&nbsp;</span><i>R. boylii</i><span>&nbsp;in an MPVA model. We compiled time series of egg mass counts (an index of adult female abundance) from&nbsp;</span><i>R. boylii</i><span>&nbsp;populations in 36 focal streams and fit an MPVA model to quantify how streamflow metrics, stream temperature, and surrounding land cover affect population growth. We found population growth was positively related to stream temperature and was higher in the years following a wet year with high total annual streamflow. Density dependence was weakest (i.e., carrying capacity was highest) for streams with high seasonality of streamflow and intermediate rates of change in streamflow during spring. Our results highlight how altered streamflow can further increase the risk of decline for&nbsp;</span><i>R. boylii</i><span>&nbsp;populations. Managing stream conditions to better match natural flow and thermal regimes would benefit the conservation of&nbsp;</span><i>R. boylii</i><span>&nbsp;populations.</span></p>","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.4645","usgsCitation":"Rose, J.P., Kupferberg, S.J., Peek, R.A., Ashton, D., Bettaso, J.B., Bobzien, S., Bourque, R.M., Breedveld, K.G., Catenazzi, A., Drennan, J.E., Gonsolin, E., Grefsrud, M., Herman, A.E., House, M.R., Kluber, M.R., Lind, A.J., Marlow, K.R., Striegle, A., van Hattem, M., Wheeler, C.A., Wilcox, J.T., Wiseman, K.D., and Halstead, B., 2023, Identifying drivers of population dynamics for a stream breeding amphibian using time series of egg mass counts: Ecosphere, v. 14, no. 8, e4645, 22 p., https://doi.org/10.1002/ecs2.4645.","productDescription":"e4645, 22 p.","ipdsId":"IP-145406","costCenters":[{"id":651,"text":"Western Ecological Research 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University","active":true,"usgs":false}],"preferred":false,"id":881272,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Drennan, Joseph E.","contributorId":328782,"corporation":false,"usgs":false,"family":"Drennan","given":"Joseph","email":"","middleInitial":"E.","affiliations":[{"id":78494,"text":"Garcia and Associates (GANDA","active":true,"usgs":false}],"preferred":false,"id":881273,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Gonsolin, Earl","contributorId":316570,"corporation":false,"usgs":false,"family":"Gonsolin","given":"Earl","email":"","affiliations":[{"id":68645,"text":"0","active":true,"usgs":false}],"preferred":false,"id":881274,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Grefsrud, Marcia","contributorId":192076,"corporation":false,"usgs":false,"family":"Grefsrud","given":"Marcia","email":"","affiliations":[],"preferred":false,"id":881275,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Herman, Andrea 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J.","contributorId":328786,"corporation":false,"usgs":false,"family":"Lind","given":"Amy","email":"","middleInitial":"J.","affiliations":[{"id":36493,"text":"USDA Forest Service","active":true,"usgs":false}],"preferred":false,"id":881279,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Marlow, Karla R.","contributorId":328787,"corporation":false,"usgs":false,"family":"Marlow","given":"Karla","email":"","middleInitial":"R.","affiliations":[{"id":78495,"text":"Garcia and Associates (GANDA),","active":true,"usgs":false}],"preferred":false,"id":881280,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Striegle, Alan","contributorId":316576,"corporation":false,"usgs":false,"family":"Striegle","given":"Alan","email":"","affiliations":[{"id":68645,"text":"0","active":true,"usgs":false}],"preferred":false,"id":881281,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"van Hattem, Michael","contributorId":316577,"corporation":false,"usgs":false,"family":"van Hattem","given":"Michael","affiliations":[{"id":68645,"text":"0","active":true,"usgs":false}],"preferred":false,"id":881282,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Wheeler, Clara A.","contributorId":328788,"corporation":false,"usgs":false,"family":"Wheeler","given":"Clara","email":"","middleInitial":"A.","affiliations":[{"id":36493,"text":"USDA Forest Service","active":true,"usgs":false}],"preferred":false,"id":881283,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Wilcox, Jeffery T.","contributorId":328789,"corporation":false,"usgs":false,"family":"Wilcox","given":"Jeffery","email":"","middleInitial":"T.","affiliations":[{"id":78496,"text":"Sonoma Mountain Ranch Preservation Foundation","active":true,"usgs":false}],"preferred":false,"id":881284,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Wiseman, Kevin D.","contributorId":328790,"corporation":false,"usgs":false,"family":"Wiseman","given":"Kevin","email":"","middleInitial":"D.","affiliations":[{"id":78497,"text":"Garcia and Associates (GANDA)","active":true,"usgs":false}],"preferred":false,"id":881285,"contributorType":{"id":1,"text":"Authors"},"rank":22},{"text":"Halstead, Brian J. 0000-0002-5535-6528 bhalstead@usgs.gov","orcid":"https://orcid.org/0000-0002-5535-6528","contributorId":3051,"corporation":false,"usgs":true,"family":"Halstead","given":"Brian J.","email":"bhalstead@usgs.gov","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":881286,"contributorType":{"id":1,"text":"Authors"},"rank":23}]}}
,{"id":70247929,"text":"70247929 - 2023 - Geographic and taxonomic variation in adaptive capacity among mountain-dwelling small mammals: implications for conservation status and actions","interactions":[],"lastModifiedDate":"2023-08-24T13:44:25.750726","indexId":"70247929","displayToPublicDate":"2023-08-24T07:57:22","publicationYear":"2023","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":"Geographic and taxonomic variation in adaptive capacity among mountain-dwelling small mammals: implications for conservation status and actions","docAbstract":"<div id=\"abstracts\" class=\"Abstracts u-font-gulliver text-s\"><div id=\"ab0005\" class=\"abstract author\" lang=\"en\"><div id=\"as0005\"><p id=\"sp0025\"><span>Contemporary climate change is modifying the distribution, morphology,&nbsp;phenology, physiology, evolution, and&nbsp;interspecific interactions&nbsp;of species.&nbsp;Effects of climate change&nbsp;are mediated not only through the magnitude of change experienced (exposure) and an animal's sensitivity to such changes, but also through the ability of the population or species to adjust to climatic variability and change genetically, behaviorally, or spatially (via its distribution) (i.e., adaptive capacity; AC). Here, we used an attribute-based framework to systematically evaluate and compare the AC of American pikas (</span><span><i>Ochotona</i><i>&nbsp;princeps</i></span>) against four other mountain-dwelling small mammals of North America to determine whether pikas are disproportionately vulnerable to climate change, as has been postulated. Unlike previous analyses, we also compared AC across<span>&nbsp;</span><i>O. princeps</i><span>&nbsp;</span>lineages and across three taxonomic (and thus, spatial) scales. Our results indicate that pikas have markedly lower adaptive capacity than all compared species except bushy-tailed woodrats (<span><i>Neotoma</i><i>&nbsp;cinerea</i></span>), and that our assessments of species generally align with earlier characterizations of climate-change vulnerability based on life-history characteristics. Although AC did not differ dramatically among pika lineages, some attributes are likely constraining AC differently in various parts of the geographic range. Comparisons across taxonomic levels of pikas illustrated that, although AC levels were comparable in pika lineages versus range-wide, AC was assessed as lower in interior-Great-Basin pikas than across the entire<span>&nbsp;</span><i>O.p. schisticeps</i><span>&nbsp;</span>lineage. We conclude that the comparatively lower AC of pikas results in particularly high susceptibility to anthropogenic climate change, corroborating results from numerous other recent investigations of pikas' climate-responsiveness. Adaptive-capacity evaluations appear useful as a consistent way to identify sentinel species or populations and for conservation prioritization.</p></div></div></div><ul id=\"issue-navigation\" class=\"issue-navigation u-margin-s-bottom u-bg-grey1\"></ul>","language":"English","publisher":"Elsevier","doi":"10.1016/j.biocon.2023.109942","usgsCitation":"Beever, E.A., Wilkening, J.L., Billman, P.D., Thurman, L., Ernest, K.A., Wright, D.H., Gill, A.M., Craighead, A.C., Helmstetter, N.A., Svancara, L.K., Camp, M.J., Bhattacharyya, S., Fitzgerald, J., Hirose, J.M., Westover, M.L., Gerraty, F.D., Klingler, K.B., Schmidt, D.A., Ryals, D.K., Brown, R.N., Clark, S., Clayton, N., Collins, G.H., Cutting, K., Doak, D.F., Epps, C., Foley, J.E., French, J., Hayes, C., Mills, Z.A., Moyer-Horner, L., Nichols, L.B., Orlofsky, K.B., Peacock, M., Penzel, N.C., Peterson, J., Ramsay, N.G., Rickman, T., Robinson, M.M., Robison, H.L., Rowe, K.M., Rowe, K.C., Russello, M., Smith, A., Stewart, J., Thompson, 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,{"id":70251919,"text":"70251919 - 2023 - Complex styles of phreatomagmatic explosions at Kīlauea Volcano, Hawaii, controlled by magma structure","interactions":[],"lastModifiedDate":"2024-03-06T12:48:01.666937","indexId":"70251919","displayToPublicDate":"2023-08-24T06:46:31","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":17169,"text":"Frontiers in Earth Science - Volcanology","active":true,"publicationSubtype":{"id":10}},"title":"Complex styles of phreatomagmatic explosions at Kīlauea Volcano, Hawaii, controlled by magma structure","docAbstract":"<div class=\"JournalAbstract\"><p class=\"mb15\">Explosive eruptions at basaltic volcanoes remain poorly understood. Kīlauea Volcano is a type locality for basaltic eruptions and is well-known for effusive activity. However, more than 7 m of phreatomagmatic Keanakākoʻi Tephra unit D deposits from explosive eruptions crown the southern rim of the summit caldera and provide a stark reminder of Kīlauea’s explosive past and future potential. We used detailed field observations as well as granulometric and morphological analysis of 100 samples from two proximal sections to assess the eruption style and fragmentation mechanism. The deposits can be divided into four subunits, six different lithofacies, and contain three juvenile tephra components. Each juvenile component shows distinct shape variability resulting from molten fuel-coolant interaction (MFCI) explosions of magma of variable vesicularity. Fragmentation of dense glass generates olive-green ash, fragmentation of low to moderately vesicular magma generates a dark gray ash-lapilli component, and fragmentation of highly vesicular magma generates light-yellow pumice. Our work shows that magma structure impacts MFCI explosion efficiency. Small-scale planar bedding throughout most of the deposit points to a general eruption style of small, frequent explosions generating low plumes. Thicker beds of accretionary lapilli of fine-extremely fine ash are related to very efficient magma-water mixing. Pyroclastic density current (PDC) deposits in the upper part of the stratigraphy contain at least three flows but show no significant dune or cross-bedding structures. We suggest that this is a function of the vent being situated in a caldera that was then ∼600 m deep, where the caldera wall acted as a barrier and changed the flow dynamics to very dilute overspills and co-PDC plume falls over the wall. Deconvolution modeling of the polymodal grain size distributions is used to assess grain size changes of each juvenile component for this deposit, which greatly improves interpretation of lithofacies generation and eruption dynamics. Size-correlated shape parameters show that shape data across a wide size range are needed to accurately track grain shapes. This study demonstrates how careful examination of grain size and shape of juvenile tephra clasts can help volcanologists understand how effusive basaltic volcanoes can become violently explosive.</p></div>","language":"English","publisher":"Frontiers","doi":"10.3389/feart.2023.1153288","usgsCitation":"Schmith, J., and Swanson, D., 2023, Complex styles of phreatomagmatic explosions at Kīlauea Volcano, Hawaii, controlled by magma structure: Frontiers in Earth Science - Volcanology, v. 11, 1153288, 25 p., https://doi.org/10.3389/feart.2023.1153288.","productDescription":"1153288, 25 p.","ipdsId":"IP-149856","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":442320,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/feart.2023.1153288","text":"Publisher Index Page"},{"id":435209,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P97WS3WS","text":"USGS data release","linkHelpText":"Keanakākoʻi Tephra unit D, Kīlauea Volcano, Hawaii: sample details, grain size, and grain shape data for 100 tephra samples"},{"id":426359,"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        \"coordinates\": [\n          [\n            [\n              -155.4259084319663,\n              19.5507272208674\n            ],\n            [\n              -155.4259084319663,\n              19.254964031182183\n            ],\n            [\n              -155.04401052855732,\n              19.254964031182183\n            ],\n            [\n              -155.04401052855732,\n              19.5507272208674\n            ],\n            [\n              -155.4259084319663,\n              19.5507272208674\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"11","noUsgsAuthors":false,"publicationDate":"2023-08-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Schmith, Jo 0000-0002-0912-7441","orcid":"https://orcid.org/0000-0002-0912-7441","contributorId":304399,"corporation":false,"usgs":true,"family":"Schmith","given":"Jo","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":896091,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Swanson, Donald A. 0000-0002-1680-3591","orcid":"https://orcid.org/0000-0002-1680-3591","contributorId":229682,"corporation":false,"usgs":true,"family":"Swanson","given":"Donald A.","affiliations":[],"preferred":true,"id":896092,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70247984,"text":"70247984 - 2023 - Evaluating a prospective fault-based stress-transfer forecast for the M7.9 Wenchuan earthquake region 15 years later","interactions":[],"lastModifiedDate":"2023-08-30T11:43:01.246632","indexId":"70247984","displayToPublicDate":"2023-08-24T06:39:23","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":10542,"text":"The Seismic Record","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating a prospective fault-based stress-transfer forecast for the M7.9 Wenchuan earthquake region 15 years later","docAbstract":"<div id=\"137789579\" class=\"article-section-wrapper js-article-section js-content-section  \" data-section-parent-id=\"0\"><p>Four days after the 12 May 2008<span>&nbsp;</span><strong>M</strong>&nbsp;7.9 Wenchuan earthquake struck the Sichuan region of China, we submitted a prospective earthquake forecast based on transfer of stress from the mainshock onto significant faults crossing through populated areas. We identified where the largest aftershocks were likely to occur that could cause loss of life. We returned the revised article to the journal on 5 June 2008, marking the last day of our observation period. The primary testable features are locations and focal mechanisms of larger (<strong>M</strong><span>&nbsp;</span>≥ 4.5) earthquakes; did these events happen on or very near the faults we said they would? Did they have the same strikes, dips, and rakes as the faults we modeled? In retrospect, is the stress transfer method consistent with all<span>&nbsp;</span><strong>M</strong><span>&nbsp;</span>≥ 4.5 earthquakes that occurred? We find all but one<span>&nbsp;</span><strong>M</strong><span>&nbsp;</span>≥ 4.5 aftershock with known focal mechanisms located on stress‐increased faults, and their focal mechanism parameters overlap with geological characteristics we used in making calculations. Six of the seven lethal<span>&nbsp;</span><strong>M</strong><span>&nbsp;</span>&gt; 4.5 earthquakes that occurred in the region since 5 June 2008 were located on stress‐increased faults, with the lone exception triggered by hydraulic fracturing.</p></div>","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0320230021","usgsCitation":"Parsons, T.E., Ji, C., and Kirby, E., 2023, Evaluating a prospective fault-based stress-transfer forecast for the M7.9 Wenchuan earthquake region 15 years later: The Seismic Record, v. 3, no. 3, p. 218-227, https://doi.org/10.1785/0320230021.","productDescription":"10 p.","startPage":"218","endPage":"227","ipdsId":"IP-153067","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":442323,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1785/0320230021","text":"Publisher Index Page"},{"id":420297,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"China","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              102.07232120934884,\n              33.52855185269891\n            ],\n            [\n              102.07232120934884,\n              30.378770167475196\n            ],\n            [\n              105.34349709659051,\n              30.378770167475196\n            ],\n            [\n              105.34349709659051,\n              33.52855185269891\n            ],\n            [\n              102.07232120934884,\n              33.52855185269891\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"3","issue":"3","noUsgsAuthors":false,"publicationDate":"2023-08-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Parsons, Thomas E. 0000-0002-0582-4338 tparsons@usgs.gov","orcid":"https://orcid.org/0000-0002-0582-4338","contributorId":2314,"corporation":false,"usgs":true,"family":"Parsons","given":"Thomas","email":"tparsons@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":881418,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ji, Chen","contributorId":62502,"corporation":false,"usgs":true,"family":"Ji","given":"Chen","email":"","affiliations":[],"preferred":false,"id":881419,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kirby, Eric 0000-0002-5701-8688","orcid":"https://orcid.org/0000-0002-5701-8688","contributorId":197171,"corporation":false,"usgs":false,"family":"Kirby","given":"Eric","email":"","affiliations":[],"preferred":false,"id":881420,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70247948,"text":"70247948 - 2023 - Multi-scale assessment of roost selection by ‘ōpe‘ape‘a, the Hawaiian hoary bat (Lasiurus semotus)","interactions":[],"lastModifiedDate":"2023-08-29T11:44:58.466128","indexId":"70247948","displayToPublicDate":"2023-08-24T06:39:17","publicationYear":"2023","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":"Multi-scale assessment of roost selection by ‘ōpe‘ape‘a, the Hawaiian hoary bat (Lasiurus semotus)","docAbstract":"<div class=\"abstract toc-section abstract-type-\"><div class=\"abstract-content\"><p>The Hawaiian hoary bat (<i>Lasiurus semotus</i>; Chiroptera: Vespertilionidae), commonly and locally known as ‘ōpe‘ape‘a, is a solitary, insectivorous, and foliage-roosting species distributed across a wide range of habitats in lowland and montane environments. The species, as with many others in the Hawaiian archipelago, are facing a suite of challenges due to habitat loss and degradation, introduced predators and pests, and climate change. An understanding of the roost requirements of foliage-roosting tree bats is critical to their conservation as these habitats provide several important benefits to survival and reproduction. Because little is known about ‘ōpe‘ape‘a roost ecology and considerable effort is needed to capture and track bats to roost locations, we examined resource selection at multiple spatial scales—perch location within a roost tree, roost tree, and forest stand. We used a discrete choice modeling approach to investigate day-roost selection and describe attributes of roost trees including those used as maternity roosts. ‘Ōpe‘ape‘a were found roosting in 19 tree species and in an assortment of landcover types including native and non-native habitats. Our results are largely consistent with findings of other studies of foliage-roosting, insectivorous tree bats where bats selected roost locations that may offer protection and thermoregulatory benefits.</p></div></div>","language":"English","publisher":"Public Library of Science","doi":"10.1371/journal.pone.0288280","usgsCitation":"Montoya-Aiona, K., Gorresen, P., Courtot, K., Aguirre, A.A., Calderon, F.A., Casler, S.P., Ciarrachi, S.G., Hoeh, J.P., Tupu, J.L., and Zinn, T.L., 2023, Multi-scale assessment of roost selection by ‘ōpe‘ape‘a, the Hawaiian hoary bat (Lasiurus semotus): PLoS ONE, v. 18, no. 8, e0288280, 25 p., https://doi.org/10.1371/journal.pone.0288280.","productDescription":"e0288280, 25 p.","ipdsId":"IP-145606","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":442326,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0288280","text":"Publisher Index Page"},{"id":435211,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9X6G081","text":"USGS data release","linkHelpText":"Hawaiʻi Island ʻōpeʻapeʻa (Hawaiian hoary bat) roost data, 2018&amp;amp;amp;amp;ndash;2021"},{"id":435210,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9G4A2E3","text":"USGS data release","linkHelpText":"Hawai&amp;amp;amp;amp;lsquo;i Island ʻōpeʻapeʻa (Hawaiian hoary bat; Lasiurus semotus) mist netting effort, capture, and tag retention, 2018&amp;amp;amp;amp;ndash;2021"},{"id":420218,"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        \"coordinates\": [\n          [\n            [\n              -156.42668817478307,\n              20.37429981764066\n            ],\n            [\n              -156.42668817478307,\n              18.72897192098766\n            ],\n            [\n              -154.63668469640746,\n              18.72897192098766\n            ],\n            [\n              -154.63668469640746,\n              20.37429981764066\n            ],\n            [\n              -156.42668817478307,\n              20.37429981764066\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"18","issue":"8","noUsgsAuthors":false,"publicationDate":"2023-08-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Montoya-Aiona, Kristina 0000-0002-1776-5443 kmontoya-aiona@usgs.gov","orcid":"https://orcid.org/0000-0002-1776-5443","contributorId":5899,"corporation":false,"usgs":true,"family":"Montoya-Aiona","given":"Kristina","email":"kmontoya-aiona@usgs.gov","affiliations":[{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true},{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"preferred":true,"id":881185,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gorresen, P. Marcos 0000-0002-0707-9212","orcid":"https://orcid.org/0000-0002-0707-9212","contributorId":196628,"corporation":false,"usgs":false,"family":"Gorresen","given":"P. Marcos","affiliations":[{"id":13341,"text":"Hawai‘i Cooperative Studies Unit, University of Hawai‘i at Hilo","active":true,"usgs":false}],"preferred":false,"id":881186,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Courtot, Karen 0000-0002-8849-4054 kcourtot@usgs.gov","orcid":"https://orcid.org/0000-0002-8849-4054","contributorId":140002,"corporation":false,"usgs":true,"family":"Courtot","given":"Karen","email":"kcourtot@usgs.gov","affiliations":[{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true},{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"preferred":true,"id":881187,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Aguirre, Aaron A. 0000-0003-2256-0669","orcid":"https://orcid.org/0000-0003-2256-0669","contributorId":328746,"corporation":false,"usgs":false,"family":"Aguirre","given":"Aaron","email":"","middleInitial":"A.","affiliations":[{"id":78479,"text":"USGS - PIERC (Formerly)","active":true,"usgs":false}],"preferred":false,"id":881188,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Calderon, Flor A. 0000-0002-9449-3648","orcid":"https://orcid.org/0000-0002-9449-3648","contributorId":328747,"corporation":false,"usgs":false,"family":"Calderon","given":"Flor","email":"","middleInitial":"A.","affiliations":[{"id":78479,"text":"USGS - PIERC (Formerly)","active":true,"usgs":false}],"preferred":false,"id":881189,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Casler, Sean P. 0000-0001-6925-439X","orcid":"https://orcid.org/0000-0001-6925-439X","contributorId":328748,"corporation":false,"usgs":false,"family":"Casler","given":"Sean","email":"","middleInitial":"P.","affiliations":[{"id":78479,"text":"USGS - PIERC (Formerly)","active":true,"usgs":false}],"preferred":false,"id":881190,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ciarrachi, Sarah G.","contributorId":328749,"corporation":false,"usgs":false,"family":"Ciarrachi","given":"Sarah","email":"","middleInitial":"G.","affiliations":[{"id":78479,"text":"USGS - PIERC (Formerly)","active":true,"usgs":false}],"preferred":false,"id":881191,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hoeh, Julia P. S. 0000-0002-4552-8779","orcid":"https://orcid.org/0000-0002-4552-8779","contributorId":328750,"corporation":false,"usgs":false,"family":"Hoeh","given":"Julia","email":"","middleInitial":"P. S.","affiliations":[{"id":78479,"text":"USGS - PIERC (Formerly)","active":true,"usgs":false}],"preferred":false,"id":881192,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Tupu, Josephine L.","contributorId":328751,"corporation":false,"usgs":false,"family":"Tupu","given":"Josephine","email":"","middleInitial":"L.","affiliations":[{"id":78481,"text":"Hawaii Cooperative Studies Unit, University of Hawaii at Hilo","active":true,"usgs":false}],"preferred":false,"id":881193,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Zinn, Terry L.","contributorId":328752,"corporation":false,"usgs":false,"family":"Zinn","given":"Terry","email":"","middleInitial":"L.","affiliations":[{"id":78479,"text":"USGS - PIERC (Formerly)","active":true,"usgs":false}],"preferred":false,"id":881194,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70247674,"text":"tm6B10 - 2023 - Parameter estimation at the conterminous United States scale and streamflow routing enhancements for the National Hydrologic Model infrastructure application of the Precipitation-Runoff Modeling System (NHM-PRMS)","interactions":[],"lastModifiedDate":"2026-03-13T15:46:27.713556","indexId":"tm6B10","displayToPublicDate":"2023-08-23T11:15:00","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":335,"text":"Techniques and Methods","code":"TM","onlineIssn":"2328-7055","printIssn":"2328-7047","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"6-B10","displayTitle":"Parameter Estimation at the Conterminous United States Scale and Streamflow Routing Enhancements for the National Hydrologic Model Infrastructure Application of the Precipitation-Runoff Modeling System (NHM-PRMS)","title":"Parameter estimation at the conterminous United States scale and streamflow routing enhancements for the National Hydrologic Model infrastructure application of the Precipitation-Runoff Modeling System (NHM-PRMS)","docAbstract":"<p>This report documents a three-part continental-scale calibration procedure and a new streamflow routing algorithm using the U.S. Geological Survey National Hydrologic Model (NHM) infrastructure along with an application of the Precipitation-Runoff Modeling System (PRMS). The traditional approach to hydrologic model calibration and evaluation, which relies on comparing observed and simulated streamflow, is not sufficient for accurately representing the non-streamflow parts of the water budget. If intermediate process variables computed by the hydrologic model are not examined, the variables could be characterized by parameter values that do not replicate those hydrological processes present in the physical system. In answer to this potential problem, alternative hydrologic process variables from the model (in addition to streamflow) are included in a calibration procedure applied to the conterminous United States (CONUS) domain.</p><p>The three-part calibration procedure presented in this report considers volume (calibration by hydrologic response unit [byHRU]), timing (calibration by headwater watershed [byHW]), and measured streamflow [byHWobs]). The first part, byHRU, is considered a water-balance volume calibration that uses five alternative (non-streamflow) hydrologic quantities (runoff, actual evapotranspiration, recharge, soil moisture, and snow-covered area) as calibration targets for each hydrologic response unit (HRU). These alternative data products were derived, with error bounds, from multiple sources for each of the 109,951 HRUs in the NHM on time scales varying from annual to daily. The second part of the calibration, byHW, is considered a streamflow timing calibration that uses statistically based streamflow simulations developed using ordinary kriging for 7,265 headwater watersheds that had drainage areas of less than 3,000 square kilometers (1,158 square miles) across the CONUS. Two streamflow routing algorithms were tested in this byHW calibration: (1) continuity without attenuation of the flood pulse and (2) a new formulation of the Muskingum routing method, which was added to the PRMS as part of this study. The third part of the calibration, byHWobs, refines the model parameters using available measured streamflow using 1,417 streamgage locations. A multiple-objective, stepwise, automated calibration procedure was used to identify the optimal set of parameters for each calibration procedure.</p><p>Using a variety of alternative datasets for calibration of the water budget provides users of the NHM-PRMS with improved initial parameters and helps alleviate the equifinality problem (getting the right answer for the wrong reason). Through a community effort, these alternative data products, with error bounds, can be used to improve and expand our understanding of hydrologic-process representation in models. The broader modeling community can use these data products, with error bounds, to calibrate and evaluate hydrologic models using more than streamflow.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm6B10","programNote":"Water Availability and Use Science Program","usgsCitation":"Hay, L.E., LaFontaine, J.H., Van Beusekom, A.E., Norton, P.A., Farmer, W.H., Regan, R.S., Markstrom, S.L., and Dickinson, J.E., 2023, Parameter estimation at the conterminous United States scale and streamflow routing enhancements for the National Hydrologic Model infrastructure application of the Precipitation-Runoff Modeling System (NHM-PRMS): U.S. Geological Survey Techniques and Methods 6–B10, 50 p., https://doi.org/10.3133/tm6B10.","productDescription":"Report: vii, 50 p.; Data Release","numberOfPages":"50","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-121885","costCenters":[{"id":13634,"text":"South Atlantic Water Science 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\"name\": \"United States\"\n      }\n    }\n  ]\n}","contact":"<p>Director, <a href=\"https://www.usgs.gov/centers/sawsc\" data-mce-href=\"https://www.usgs.gov/centers/sawsc\">South Atlantic Water Science Center</a><br>U.S. Geological Survey<br>1770 Corporate Drive, Suite 500<br>Norcross, GA 30093</p><p><a href=\"https://pubs.er.usgs.gov/contact\" data-mce-href=\"../contact\">Contact Pubs Warehouse</a></p>","tableOfContents":"<ul><li>Abstract</li><li>Introduction</li><li>Methods</li><li>Results</li><li>Limitations of NHM-PRMS Modeling Application</li><li>Summary</li><li>Acknowledgments</li><li>References Cited</li><li>Appendix 1. National Hydrologic Model Infrastructure Application of the Precipitation-Runoff Modeling System (NHM-PRMS) Calibration Setup</li><li>Appendix 2. Documentation of the muskingum_mann Streamflow Routing Module for the Precipitation-Runoff Modeling System</li></ul>","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2023-08-23","noUsgsAuthors":false,"publicationDate":"2023-08-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Hay, Lauren E. 0000-0003-3763-4595","orcid":"https://orcid.org/0000-0003-3763-4595","contributorId":225584,"corporation":false,"usgs":false,"family":"Hay","given":"Lauren E.","affiliations":[{"id":39981,"text":"private consultant","active":true,"usgs":false}],"preferred":false,"id":880003,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"LaFontaine, Jacob H. 0000-0003-4923-2630 jlafonta@usgs.gov","orcid":"https://orcid.org/0000-0003-4923-2630","contributorId":2258,"corporation":false,"usgs":true,"family":"LaFontaine","given":"Jacob","email":"jlafonta@usgs.gov","middleInitial":"H.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":316,"text":"Georgia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":880004,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Van Beusekom, Ashley E. 0000-0002-6996-978X beusekom@usgs.gov","orcid":"https://orcid.org/0000-0002-6996-978X","contributorId":3992,"corporation":false,"usgs":true,"family":"Van Beusekom","given":"Ashley","email":"beusekom@usgs.gov","middleInitial":"E.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":880089,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Norton, Parker A. 0000-0002-4638-2601 pnorton@usgs.gov","orcid":"https://orcid.org/0000-0002-4638-2601","contributorId":2257,"corporation":false,"usgs":true,"family":"Norton","given":"Parker","email":"pnorton@usgs.gov","middleInitial":"A.","affiliations":[{"id":562,"text":"South Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":880090,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Farmer, William H. 0000-0002-2865-2196","orcid":"https://orcid.org/0000-0002-2865-2196","contributorId":223181,"corporation":false,"usgs":true,"family":"Farmer","given":"William H.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":880007,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Regan, R. Steve 0000-0003-4803-8596 rsregan@usgs.gov","orcid":"https://orcid.org/0000-0003-4803-8596","contributorId":196973,"corporation":false,"usgs":true,"family":"Regan","given":"R.","email":"rsregan@usgs.gov","middleInitial":"Steve","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":880008,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Markstrom, Steven L. 0000-0001-7630-9547 markstro@usgs.gov","orcid":"https://orcid.org/0000-0001-7630-9547","contributorId":146553,"corporation":false,"usgs":true,"family":"Markstrom","given":"Steven","email":"markstro@usgs.gov","middleInitial":"L.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":880009,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Dickinson, Jesse E. 0000-0002-0048-0839 jdickins@usgs.gov","orcid":"https://orcid.org/0000-0002-0048-0839","contributorId":152545,"corporation":false,"usgs":true,"family":"Dickinson","given":"Jesse","email":"jdickins@usgs.gov","middleInitial":"E.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":880091,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70254450,"text":"70254450 - 2023 - Fluid migration pathways to groundwater in mature oil fields: Exploring the roles of water injection/production and oil-well integrity in California, USA","interactions":[],"lastModifiedDate":"2024-05-24T11:45:46.389957","indexId":"70254450","displayToPublicDate":"2023-08-23T06:43:14","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Fluid migration pathways to groundwater in mature oil fields: Exploring the roles of water injection/production and oil-well integrity in California, USA","docAbstract":"<div id=\"ab0005\" class=\"abstract author\" lang=\"en\"><div id=\"as0005\"><p id=\"sp0045\"><span>Mature oil fields potentially contain multiple fluid migration pathways toward protected groundwater (total dissolved solids, TDS, in nonexempted aquifer &lt;10,000&nbsp;mg/L) because of their extensive development histories. Time-series data for water use, fluid pressures, oil-well construction, and&nbsp;geochemistry&nbsp;from the South Belridge and Lost Hills mature oil fields in California are used to explore the roles of injection/production of oil-field water and well-integrity issues in fluid migration. Injection/production of oil-field water modified hydraulic gradients in both oil fields, resulting in chemical transport from deeper groundwater and hydrocarbon-reservoir systems to aquifers in the oil fields. Those aquifers are used for&nbsp;</span>water supply<span>&nbsp;outside the oil-field boundaries. Oil wells drilled before 1976 can be fluid migration pathways because a relatively large percentage of them have &gt;10&nbsp;m of uncemented annulus that straddles oil-well casing damage and/or the base of groundwater with TDS &lt;10,000&nbsp;mg/L. The risk of groundwater-quality degradation is higher when wells with those risk factors occur in areas with upward hydraulic gradients created by positive net injection, groundwater withdrawals, or combinations of these variables. The complex changes in hydrologic conditions and&nbsp;groundwater chemistry&nbsp;likely would not have been discovered in the absence of years to decades of monitoring data for groundwater elevations and chemistry, and installation of monitoring wells in areas with overlapping risk factors. Important monitoring concepts based on results from this and other studies include monitoring hydrocarbon-reservoir and groundwater systems at multiple spatiotemporal scales and maintaining transparency and accessibility of data and analyses. This analysis focuses on two California oil fields, but the methods used and processes affecting fluid migration could be relevant in other oil fields where substantial injection/production of oil-field water occurs and oil-well integrity is of concern.</span></p></div></div><div id=\"ab0010\" class=\"abstract graphical\" lang=\"en\"><br></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2023.166400","usgsCitation":"McMahon, P.B., Landon, M.K., Stephens, M.J., Taylor, K.A., Gillespie, J.M., Davis, T., and Shimabukuro, D.H., 2023, Fluid migration pathways to groundwater in mature oil fields: Exploring the roles of water injection/production and oil-well integrity in California, USA: Science of the Total Environment, v. 900, 166400, 15 p., https://doi.org/10.1016/j.scitotenv.2023.166400.","productDescription":"166400, 15 p.","ipdsId":"IP-148641","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":442333,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2023.166400","text":"Publisher Index Page"},{"id":435212,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9MHSTGS","text":"USGS data release","linkHelpText":"Oil well annular cement and casing damage data in mature oil fields undergoing hydraulic fracturing, South Belridge and Lost Hills Oil Fields, California"},{"id":429240,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              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ktaylor@usgs.gov","orcid":"https://orcid.org/0000-0002-0095-6403","contributorId":1601,"corporation":false,"usgs":true,"family":"Taylor","given":"Kimberly","email":"ktaylor@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":901405,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gillespie, Janice M. 0000-0003-1667-3472","orcid":"https://orcid.org/0000-0003-1667-3472","contributorId":219675,"corporation":false,"usgs":true,"family":"Gillespie","given":"Janice","email":"","middleInitial":"M.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":901406,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Davis, Tracy 0000-0003-0253-6661 tadavis@usgs.gov","orcid":"https://orcid.org/0000-0003-0253-6661","contributorId":176921,"corporation":false,"usgs":true,"family":"Davis","given":"Tracy","email":"tadavis@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":901407,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Shimabukuro, David H. 0000-0002-6106-5284","orcid":"https://orcid.org/0000-0002-6106-5284","contributorId":208209,"corporation":false,"usgs":false,"family":"Shimabukuro","given":"David","email":"","middleInitial":"H.","affiliations":[{"id":37762,"text":"California State University, Sacramento","active":true,"usgs":false}],"preferred":false,"id":901408,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70247743,"text":"dr1180 - 2023 - Calibrating optical turbidity measurements with suspended-sediment concentrations from the Herring River in Wellfleet, Massachusetts, from November 2018 to November 2019","interactions":[],"lastModifiedDate":"2026-02-04T20:13:58.477377","indexId":"dr1180","displayToPublicDate":"2023-08-22T15:20:00","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":9318,"text":"Data Report","code":"DR","onlineIssn":"2771-9448","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1180","displayTitle":"Calibrating Optical Turbidity Measurements with Suspended-Sediment Concentrations from the Herring River in Wellfleet, Massachusetts, from November 2018 to November 2019","title":"Calibrating optical turbidity measurements with suspended-sediment concentrations from the Herring River in Wellfleet, Massachusetts, from November 2018 to November 2019","docAbstract":"The sediment budget in the tidally restricted Herring River in Wellfleet, Massachusetts, must be quantified so restoration options for the river can be evaluated. Platforms equipped with optical turbidity sensors were deployed seaward and landward of the Herring River restriction to measure a time series of turbidity, from which a time series of suspended-sediment concentration (SSC) can be estimated. Water samples were collected periodically from the Herring River from November 2018 to November 2019 and analyzed for SSC to derive a relationship to turbidity measurements given in nephelometric turbidity units. This report presents the data-collection methods used and the linear calibration model generated by repeated median regression to convert turbidity measurements to SSC.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/dr1180","programNote":"Coastal and Marine Hazards and Resources Program","usgsCitation":"De Meo, O.A., Ganju, N.K., Bales, R.D., Marsjanik, E.D., and Suttles, S.E., 2023, Calibrating optical turbidity measurements with suspended-sediment concentrations from the Herring River in Wellfleet, Massachusetts, from November 2018 to November 2019: U.S. Geological Survey Data Report 1180, 8 p., https://doi.org/10.3133/dr1180.","productDescription":"Report: vi, 8 p.; 3 Data Releases","numberOfPages":"8","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-150029","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":499555,"rank":9,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115238.htm","linkFileType":{"id":5,"text":"html"}},{"id":419963,"rank":8,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/dr/1180/images/"},{"id":419962,"rank":7,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/dr/1180/dr1180.XML"},{"id":419824,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9K3SCKY","text":"USGS data release","linkHelpText":"Water quality data from a multiparameter sonde collected in the Herring River during November 2018 to November 2019 in Wellfleet, MA"},{"id":419823,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P95AE74D","text":"USGS data release","linkHelpText":"Time-series measurements of oceanographic and water quality data collected in the Herring River, Wellfleet, Massachusetts, USA, November 2018 to November 2019"},{"id":419822,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9ZL2IPN","text":"USGS data release","linkHelpText":"Suspended-sediment concentrations and loss-on-ignition from water samples collected in the Herring River during 2018-19 in Wellfleet, MA (ver 1.1, March 2023)"},{"id":419961,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/dr1180/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"DR 1180"},{"id":419821,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/dr/1180/dr1180.pdf","text":"Report","size":"4.57 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DR 1180"},{"id":419820,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/dr/1180/coverthb.jpg"}],"country":"United States","state":"Massachusetts","city":"Wellfleet","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -70.08466148489833,\n              41.94504968532215\n            ],\n            [\n              -70.08466148489833,\n              41.912369414289856\n            ],\n            [\n              -70.04897123149479,\n              41.912369414289856\n            ],\n            [\n              -70.04897123149479,\n              41.94504968532215\n            ],\n            [\n              -70.08466148489833,\n              41.94504968532215\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","contact":"<p><a href=\"mailto:WHSC_ science_ director@usgs.gov\" data-mce-href=\"mailto:WHSC_ science_ director@usgs.gov\">Director</a>, <a href=\"https://www.usgs.gov/centers/whcmsc\" data-mce-href=\"https://www.usgs.gov/centers/whcmsc\">Woods Hole Coastal and Marine Science Center</a><br>U.S. Geological Survey<br>384 Woods Hole Road<br>Quissett Campus<br>Woods Hole, MA 02543-1598</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Sensor Deployment and Water Sample Collection</li><li>Laboratory Determination of Suspended-Sediment Concentration</li><li>Calibration of the Optical Turbidity Sensor</li><li>Summary</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"publishedDate":"2023-08-22","noUsgsAuthors":false,"publicationDate":"2023-08-22","publicationStatus":"PW","contributors":{"authors":[{"text":"De Meo, Olivia A. 0000-0003-3937-1354","orcid":"https://orcid.org/0000-0003-3937-1354","contributorId":300810,"corporation":false,"usgs":true,"family":"De Meo","given":"Olivia","email":"","middleInitial":"A.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":880229,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ganju, Neil K. 0000-0002-1096-0465","orcid":"https://orcid.org/0000-0002-1096-0465","contributorId":202878,"corporation":false,"usgs":true,"family":"Ganju","given":"Neil K.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":880230,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bales, Robert D. 0000-0002-0807-9804","orcid":"https://orcid.org/0000-0002-0807-9804","contributorId":296652,"corporation":false,"usgs":true,"family":"Bales","given":"Robert","email":"","middleInitial":"D.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":880231,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Marsjanik, Eric D. 0000-0002-6065-0182 emarsjanik@usgs.gov","orcid":"https://orcid.org/0000-0002-6065-0182","contributorId":195777,"corporation":false,"usgs":true,"family":"Marsjanik","given":"Eric","email":"emarsjanik@usgs.gov","middleInitial":"D.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":880232,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Suttles, Steven E. 0000-0002-4119-8370 ssuttles@usgs.gov","orcid":"https://orcid.org/0000-0002-4119-8370","contributorId":192272,"corporation":false,"usgs":true,"family":"Suttles","given":"Steven","email":"ssuttles@usgs.gov","middleInitial":"E.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":880233,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70247877,"text":"sim3505 - 2023 - Aeromagnetic map of northeastern California","interactions":[],"lastModifiedDate":"2026-02-19T17:58:59.83292","indexId":"sim3505","displayToPublicDate":"2023-08-22T12:32:17","publicationYear":"2023","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":"3505","displayTitle":"Aeromagnetic Map of Northeastern California","title":"Aeromagnetic map of northeastern California","docAbstract":"<p>Aeromagnetic surveys were conducted to improve understanding of the geology and structure in northeastern California, a region predominantly covered by Quaternary and Tertiary, mainly Neogene, volcanic rocks including Medicine Lake volcano. New aeromagnetic data are a substantial improvement over existing data and reveal structural details not resolved by older surveys. Here we show how these data (1) do not support the presence of a northwest-striking structural feature across the Modoc Plateau, (2) reveal a northeast-striking fault-bounded block of predominantly reversely magnetized material that may influence tectonism at Medicine Lake volcano, and (3) constrain possible right-lateral offsets along the Likely Fault Zone and other faults that traverse the region. The data also highlight possible extensions of mapped faults, such as those in Fall River Valley and the Tule and Lower Klamath Lake areas.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3505","usgsCitation":"Langenheim, V.E. and Sweetkind, D.S., 2023, Aeromagnetic map of northeastern California: U.S. Geological Survey Scientific Investigations Map 3505, pamphlet 21 p., https://doi.org/10.3133/sim3505.","productDescription":"Pamphlet: iv, 21 p.; 3 Data Releases; 1 Sheet: 30.82 × 39.53 inches","numberOfPages":"21","additionalOnlineFiles":"Y","ipdsId":"IP-137584","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":500211,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115218.htm","linkFileType":{"id":5,"text":"html"}},{"id":435213,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9TQGRDW","text":"USGS data release","linkHelpText":"Aeromagnetic and derivative gridded data, and magnetization boundaries of northeastern California"},{"id":420034,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P91Y9L0H","text":"Data release of geologic data for the aeromagnetic map of northeastern California","description":"Sweetkind, D.S., and Langenheim, V.E., 2022, Data release of geologic data for the aeromagnetic map of northeastern California: U.S. Geological Survey data release, https://doi.org/10.5066/P91Y9L0H."},{"id":420033,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9PUFYDD","text":"Aeromagnetic and derivative gridded data, and magnetization boundaries of northeastern California","description":"Langenheim, V.E., 2023, Aeromagnetic and derivative gridded data, and magnetization boundaries of northeastern California: U.S. Geological data release, https://doi.org/10.5066/P9PUFYDD."},{"id":420032,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9LU37RC","text":"Aeromagnetic Data of Alturas, California, and Surrounding Areas","description":"Langenheim, V.E., 2022, Aeromagnetic Data of Alturas, California, and Surrounding Areas: U.S. Geological Survey data release, https://doi.org/10.5066/P9LU37RC."},{"id":420031,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3505/sim3505_sheet.pdf","text":"Map Sheet","size":"30 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":420030,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3505/sim3505_pamphlet.pdf","text":"Pamphlet","size":"10 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":420029,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3505/covrthb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -120.03188053680955,\n              42.02157881382186\n            ],\n            [\n              -122.00857149452494,\n              42.02157881382186\n            ],\n            [\n              -122.00857149452494,\n              40.50279454574354\n            ],\n            [\n              -120.03188053680955,\n              40.50279454574354\n            ],\n            [\n              -120.03188053680955,\n              42.02157881382186\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","contact":"<p><a href=\"https://www.usgs.gov/centers/gmeg\" data-mce-href=\"https://www.usgs.gov/centers/gmeg\">Geology, Minerals, Energy, &amp; Geophysics Science Center</a><br><a href=\"https://gcc02.safelinks.protection.outlook.com/?url=https%3A%2F%2Fusgs.gov%2F&amp;data=05%7C01%7Cjtran%40usgs.gov%7C2acc9ccfe04c490508e208db57150e3b%7C0693b5ba4b184d7b9341f32f400a5494%7C0%7C0%7C638199520171483214%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&amp;sdata=M5pIPYGVMGFOGVgSlKnAjJ%2FMw0n5BBDivZ0f4E1wjFs%3D&amp;reserved=0\" data-mce-href=\"https://gcc02.safelinks.protection.outlook.com/?url=https%3A%2F%2Fusgs.gov%2F&amp;data=05%7C01%7Cjtran%40usgs.gov%7C2acc9ccfe04c490508e208db57150e3b%7C0693b5ba4b184d7b9341f32f400a5494%7C0%7C0%7C638199520171483214%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&amp;sdata=M5pIPYGVMGFOGVgSlKnAjJ%2FMw0n5BBDivZ0f4E1wjFs%3D&amp;reserved=0\">U.S. Geological Survey</a><br>Building 19, 350 N. Akron Rd.<br>P.O. Box 158<br>Moffett Field, CA 94035</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Data</li><li>Filtering and Magnetization Boundaries</li><li>Results</li><li>Description of Map Units</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"publishedDate":"2023-08-22","noUsgsAuthors":false,"publicationDate":"2023-08-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Langenheim, Victoria E. 0000-0003-2170-5213 zulanger@usgs.gov","orcid":"https://orcid.org/0000-0003-2170-5213","contributorId":151042,"corporation":false,"usgs":true,"family":"Langenheim","given":"Victoria E.","email":"zulanger@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":880839,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sweetkind, Donald S. 0000-0003-0892-4796 dsweetkind@usgs.gov","orcid":"https://orcid.org/0000-0003-0892-4796","contributorId":139913,"corporation":false,"usgs":true,"family":"Sweetkind","given":"Donald","email":"dsweetkind@usgs.gov","middleInitial":"S.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":880840,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70247907,"text":"70247907 - 2023 - Mechanisms of water-rock interaction and implications for remediating flooded mine workings elucidated from environmental tracers, stable isotopes, and rare earth elements","interactions":[],"lastModifiedDate":"2023-08-24T12:07:58.586956","indexId":"70247907","displayToPublicDate":"2023-08-19T07:05:13","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":835,"text":"Applied Geochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Mechanisms of water-rock interaction and implications for remediating flooded mine workings elucidated from environmental tracers, stable isotopes, and rare earth elements","docAbstract":"<div id=\"abs0010\" class=\"abstract author\" lang=\"en\"><div id=\"abssec0010\"><p id=\"abspara0010\"><span>Contamination from&nbsp;acid mine drainage&nbsp;affects ecosystems and usability of groundwater for domestic and municipal purposes. The Captain Jack&nbsp;Superfund Site&nbsp;outside of Ward, Boulder County, Colorado,&nbsp;USA, hosts a draining mine adit that was remediated through emplacement of a hydraulic bulkhead to preclude acid mine drainage from entering nearby Lefthand Creek. During impoundment of water within the mine workings in 2020, a diverse and novel dataset of&nbsp;stable isotopes&nbsp;of water, sulfate, and carbon (δ</span><sup>2</sup>H, δ<sup>18</sup>O<sub>H2O</sub>, δ<sup>18</sup>O<sub>SO4</sub>, δ<sup>34</sup>S, δ<sup>13</sup>C<sub>DIC</sub><span>),&nbsp;rare earth elements, and environmental tracers (noble gases and tritium) were collected to understand&nbsp;groundwater recharge&nbsp;and mixing, mechanisms of sulfide oxidation and water-rock interaction, and the influence of remediation on the hydrologic and geochemical system.&nbsp;Water isotopes&nbsp;indicate that groundwater distal from the mine workings has seasonally variable recharge sources whereas water within the workings has a distinctive composition with minimal temporal variability. Sulfate isotopes indicate that sulfide oxidation occurs both within the mine workings and in adjacent igneous&nbsp;dikes, and that sulfide oxidation may occur under&nbsp;suboxic conditions&nbsp;with ferric iron as the oxidant. Carbon isotopes track the neutralization of acidic waters and the carbon mass budget of the system. Rare earth elements corroborate stable isotopes in indicating groundwater compartmentalization, and additionally illustrate enhanced mineral weathering in the mine workings. Environmental tracers indicate mixing of modern and pre-modern groundwater and inform timelines that active remediation may be needed. Together these datasets provide a useful template for similar investigations of abandoned mine sites where physical mixing processes, sources of solute loading, or remediation timeframes are of importance.</span></p></div></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.apgeochem.2023.105769","usgsCitation":"Newman, C.P., Walton-Day, K., Runkel, R.L., and Wilkin, R., 2023, Mechanisms of water-rock interaction and implications for remediating flooded mine workings elucidated from environmental tracers, stable isotopes, and rare earth elements: Applied Geochemistry, v. 157, 105769, 15 p., https://doi.org/10.1016/j.apgeochem.2023.105769.","productDescription":"105769, 15 p.","ipdsId":"IP-131195","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":442354,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/10631561","text":"Publisher Index 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,{"id":70247843,"text":"70247843 - 2023 - Societal benefits of floodplains in the Chesapeake Bay and Delaware River watersheds: Sediment, nutrient, and flood regulation ecosystem services","interactions":[],"lastModifiedDate":"2023-11-28T14:47:07.715993","indexId":"70247843","displayToPublicDate":"2023-08-19T06:48:08","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2258,"text":"Journal of Environmental Management","active":true,"publicationSubtype":{"id":10}},"title":"Societal benefits of floodplains in the Chesapeake Bay and Delaware River watersheds: Sediment, nutrient, and flood regulation ecosystem services","docAbstract":"<p>Floodplains provide critical ecosystem services to people by regulating floodwaters and retaining sediments and nutrients. Geospatial analyses, field data collection, and modeling were integrated to quantify a portfolio of services that floodplains provide to downstream communities within the Chesapeake Bay and Delaware River watersheds. The portfolio of services included floodplain sediment and nutrient retention and flood regulation. Sediment and nutrient retention were quantified and valued for all non-tidal wadable streams in the Chesapeake Bay and Delaware River watersheds. Predicted nitrogen fluxes from measurements of streambanks and floodplain geomorphic changes were summarized at various scales (river basin, state, and county) and valued using a benefits transfer approach. Floodplain flood regulation services were assessed through a pilot study focused on the Schuylkill River watershed in the Delaware River watershed. Geospatial analysis and published flood frequency estimates were used to assess baseline and counterfactual (i.e., floodplain storage removed) scenarios. Flood regulation was valued using the Federal Emergency Management Agency's Hazus model to compare differences in structural damage to private residences under baseline and counterfactual scenarios. The estimated value of floodplain sediment and nutrient retention was \\$223 million United States dollars (USD) per year in the Chesapeake Bay watershed and \\$38 million USD per year in the Delaware River watershed. Sediment and nutrient retention benefits were offset by a streambank erosion cost of \\$123 million and \\$14 million USD annually in the Chesapeake and Delaware watersheds, respectively. In the Schuylkill River watershed floodplain flood regulation was valued at \\$860,000 USD per year, with an additional \\$7.2 million USD annually provided through floodplain sediment and nutrient retention. Together this portfolio of floodplain ecosystem services indicates that floodplains provide substantial benefits to people by trapping nutrients and storing floodwaters.</p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jenvman.2023.118747","usgsCitation":"Hopkins, K.G., Welles, J.S., Pindilli, E., Noe, G.E., Claggett, P., Ahmed, L., and Metes, M.J., 2023, Societal benefits of floodplains in the Chesapeake Bay and Delaware River watersheds: Sediment, nutrient, and flood regulation ecosystem services: Journal of Environmental Management, v. 345, 118747, 16 p., https://doi.org/10.1016/j.jenvman.2023.118747.","productDescription":"118747, 16 p.","ipdsId":"IP-152558","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":442357,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jenvman.2023.118747","text":"Publisher Index 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khopkins@usgs.gov","orcid":"https://orcid.org/0000-0003-1699-9384","contributorId":195604,"corporation":false,"usgs":true,"family":"Hopkins","given":"Kristina","email":"khopkins@usgs.gov","middleInitial":"G.","affiliations":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":880730,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Welles, Jacqueline Sage 0000-0001-9218-4369","orcid":"https://orcid.org/0000-0001-9218-4369","contributorId":328592,"corporation":false,"usgs":true,"family":"Welles","given":"Jacqueline","email":"","middleInitial":"Sage","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":880731,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pindilli, Emily 0000-0002-5101-1266 epindilli@usgs.gov","orcid":"https://orcid.org/0000-0002-5101-1266","contributorId":140262,"corporation":false,"usgs":true,"family":"Pindilli","given":"Emily","email":"epindilli@usgs.gov","affiliations":[{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true}],"preferred":true,"id":880732,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Noe, Gregory E. 0000-0002-6661-2646 gnoe@usgs.gov","orcid":"https://orcid.org/0000-0002-6661-2646","contributorId":139100,"corporation":false,"usgs":true,"family":"Noe","given":"Gregory","email":"gnoe@usgs.gov","middleInitial":"E.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":880733,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Claggett, Peter 0000-0002-5335-2857","orcid":"https://orcid.org/0000-0002-5335-2857","contributorId":238920,"corporation":false,"usgs":true,"family":"Claggett","given":"Peter","affiliations":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":880734,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ahmed, Labeeb 0000-0003-4524-9611","orcid":"https://orcid.org/0000-0003-4524-9611","contributorId":303117,"corporation":false,"usgs":true,"family":"Ahmed","given":"Labeeb","email":"","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":880735,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Metes, Marina J. 0000-0002-6797-9837","orcid":"https://orcid.org/0000-0002-6797-9837","contributorId":204835,"corporation":false,"usgs":true,"family":"Metes","given":"Marina","middleInitial":"J.","affiliations":[{"id":41514,"text":"Maryland-Delaware-District of Columbia  Water Science Center","active":true,"usgs":true}],"preferred":true,"id":880736,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70249844,"text":"70249844 - 2023 - Ground‐motion variability from kinematic rupture models and the implications for nonergodic probabilistic seismic hazard analysis","interactions":[],"lastModifiedDate":"2023-11-02T14:54:05.009294","indexId":"70249844","displayToPublicDate":"2023-08-18T09:46:52","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"Ground‐motion variability from kinematic rupture models and the implications for nonergodic probabilistic seismic hazard analysis","docAbstract":"<p><span>The variability of earthquake ground motions has a strong control on probabilistic seismic hazard analysis (PSHA), particularly for the low frequencies of exceedance used for critical facilities. We use a crossed mixed‐effects model to partition the variance components from simulated ground motions of&nbsp;</span><strong><i><span class=\"inline-formula no-formula-id\"><span id=\"MathJax-Element-1-Frame\" class=\"MathJax\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><msub xmlns=&quot;&quot;><mi>M</mi><mi mathvariant=&quot;normal&quot;>w</mi></msub></math>\"><span id=\"MathJax-Span-1\" class=\"math\"><span id=\"MathJax-Span-2\" class=\"mrow\"><span id=\"MathJax-Span-3\" class=\"msub\"><span id=\"MathJax-Span-4\" class=\"mi\">M</span><sub><span id=\"MathJax-Span-5\" class=\"mi\">w</span></sub></span></span></span></span></span></i></strong><span>&nbsp;7 earthquakes on the Salt Lake City segment of the Wasatch fault zone. Total variability of simulated ground motions is approximately equivalent to empirical models. The high contribution from rupture speed suggests an avenue to reducing variability through research on the causes and predictions of rupture speed on specific faults. Simulations show a strong spatial heterogeneity in the variability that manifests from directivity effects. We illustrate the impact of this spatial heterogeneity on hazard using a partially nonergodic PSHA framework. The results highlight the benefit of accounting for directivity effects in nonergodic PSHA, in which models that account for additional processes controlling ground motions are paired with reductions in the modeled ground‐motion variability.</span></p>","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220220380","usgsCitation":"Parker, G.A., Moschetti, M.P., and Thompson, E.M., 2023, Ground‐motion variability from kinematic rupture models and the implications for nonergodic probabilistic seismic hazard analysis: Seismological Research Letters, v. 94, no. 6, p. 2687-2697, https://doi.org/10.1785/0220220380.","productDescription":"11 p.","startPage":"2687","endPage":"2697","ipdsId":"IP-142964","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":422337,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Salt Lake City segment of the Wasatch fault zone","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -112.5,\n              41.25\n            ],\n            [\n              -112.5,\n              39.75\n            ],\n            [\n              -111.4,\n              39.75\n            ],\n            [\n              -111.4,\n              41.25\n            ],\n            [\n              -112.5,\n              41.25\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"94","issue":"6","noUsgsAuthors":false,"publicationDate":"2023-08-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Parker, Grace Alexandra 0000-0002-9445-2571","orcid":"https://orcid.org/0000-0002-9445-2571","contributorId":237091,"corporation":false,"usgs":true,"family":"Parker","given":"Grace","email":"","middleInitial":"Alexandra","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":887358,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Moschetti, Morgan P. 0000-0001-7261-0295 mmoschetti@usgs.gov","orcid":"https://orcid.org/0000-0001-7261-0295","contributorId":1662,"corporation":false,"usgs":true,"family":"Moschetti","given":"Morgan","email":"mmoschetti@usgs.gov","middleInitial":"P.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":887359,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thompson, Eric M. 0000-0002-6943-4806 emthompson@usgs.gov","orcid":"https://orcid.org/0000-0002-6943-4806","contributorId":150897,"corporation":false,"usgs":true,"family":"Thompson","given":"Eric","email":"emthompson@usgs.gov","middleInitial":"M.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":887360,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70247852,"text":"70247852 - 2023 - Runout model evaluation based on back-calculation of building damage","interactions":[],"lastModifiedDate":"2023-08-23T10:59:31.85972","indexId":"70247852","displayToPublicDate":"2023-08-18T09:17:24","publicationYear":"2023","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Runout model evaluation based on back-calculation of building damage","docAbstract":"We evaluated the ability of three debris-flow runout models (RAMMS, FLO2D and D-Claw) to\npredict the number of damaged buildings in simulations of the 9 January 2019 Montecito, California, debris-flow event. Observations of building damage after the event were combined with OpenStreetMap building footprints to construct a database of all potentially impacted buildings. At the estimated event volume, all models overpredict the number of damaged buildings by a factor of 1.5–3.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"E3S Web of Conferences","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"2023 8th International Conference on Debris Flow Hazard Mitigation (DFHM8)","conferenceDate":"June 26-29, 2023","conferenceLocation":"Turin, Italy","language":"English","publisher":"EDP Sciences","doi":"10.1051/e3sconf/202341507001","usgsCitation":"Barnhart, K.R., and Kean, J.W., 2023, Runout model evaluation based on back-calculation of building damage, <i>in</i> E3S Web of Conferences, v. 415, Turin, Italy, June 26-29, 2023, 07001, 4 p., https://doi.org/10.1051/e3sconf/202341507001.","productDescription":"07001, 4 p.","ipdsId":"IP-142508","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":442368,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"http://dx.doi.org/10.1051/e3sconf/202341507001","text":"Publisher Index Page"},{"id":420016,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","city":"Montecito","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -119.66612886667129,\n              34.46992292512056\n            ],\n            [\n              -119.66612886667129,\n              34.4075932985982\n            ],\n            [\n              -119.57147580590843,\n              34.4075932985982\n            ],\n            [\n              -119.57147580590843,\n              34.46992292512056\n            ],\n            [\n              -119.66612886667129,\n              34.46992292512056\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"415","noUsgsAuthors":false,"publicationDate":"2023-08-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Barnhart, Katherine R. 0000-0001-5682-455X","orcid":"https://orcid.org/0000-0001-5682-455X","contributorId":257870,"corporation":false,"usgs":true,"family":"Barnhart","given":"Katherine","email":"","middleInitial":"R.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":880750,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kean, Jason W. 0000-0003-3089-0369 jwkean@usgs.gov","orcid":"https://orcid.org/0000-0003-3089-0369","contributorId":1654,"corporation":false,"usgs":true,"family":"Kean","given":"Jason","email":"jwkean@usgs.gov","middleInitial":"W.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":880751,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70247849,"text":"70247849 - 2023 - Forecasting the inundation of postfire debris flows","interactions":[],"lastModifiedDate":"2023-08-22T14:19:38.055802","indexId":"70247849","displayToPublicDate":"2023-08-18T09:08:48","publicationYear":"2023","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Forecasting the inundation of postfire debris flows","docAbstract":"In the semi-arid regions of the western United States, postfire debris flows are typically runoff\ngenerated. The U.S. Geological Survey has been studying the mechanisms of postfire debris-flow initiation for multiple decades to generate operational models for forecasting the timing, location, and magnitude of postfire debris flows. Here we discuss challenges and progress for extending operational capabilities to include modeling postfire debris-flow inundation extent. Analysis of volume and impacted area scaling relationships indicated that postfire debris flows do not conform to assumptions of geometric self-similarity. We documented sensitivity of impacted areas to rainfall intensity using a candidate methodology for generating inundation hazard assessments. Our results emphasize the importance of direct measurements of debris-flow volume, inundated area, and high temporal resolution rainfall intensity.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"E3S Web of Conferences","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"2023 8th International Conference on Debris Flow Hazard Mitigation (DFHM8)","conferenceDate":"June 26-29, 2023","conferenceLocation":"Turin, Italy","language":"English","publisher":"EDP Sciences","doi":"10.1051/e3sconf/202341504002","usgsCitation":"Barnhart, K.R., Jones, R., George, D.L., Rengers, F.K., and Kean, J.W., 2023, Forecasting the inundation of postfire debris flows, <i>in</i> E3S Web of Conferences, v. 415, Turin, Italy, June 26-29, 2023, 04002, 4 p., https://doi.org/10.1051/e3sconf/202341504002.","productDescription":"04002, 4 p.","ipdsId":"IP-146470","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":442370,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1051/e3sconf/202341504002","text":"Publisher Index Page"},{"id":420015,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","city":"Montecito","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -119.66612886667129,\n              34.46992292512056\n            ],\n            [\n              -119.66612886667129,\n              34.4075932985982\n            ],\n            [\n              -119.57147580590843,\n              34.4075932985982\n            ],\n            [\n              -119.57147580590843,\n              34.46992292512056\n            ],\n            [\n              -119.66612886667129,\n              34.46992292512056\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"415","noUsgsAuthors":false,"publicationDate":"2023-08-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Barnhart, Katherine R. 0000-0001-5682-455X","orcid":"https://orcid.org/0000-0001-5682-455X","contributorId":257870,"corporation":false,"usgs":true,"family":"Barnhart","given":"Katherine","email":"","middleInitial":"R.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":880741,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jones, Ryan P 0000-0001-6363-7592","orcid":"https://orcid.org/0000-0001-6363-7592","contributorId":328597,"corporation":false,"usgs":false,"family":"Jones","given":"Ryan P","affiliations":[{"id":78420,"text":"Flow Science","active":true,"usgs":false}],"preferred":false,"id":880742,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"George, David L. 0000-0002-5726-0255 dgeorge@usgs.gov","orcid":"https://orcid.org/0000-0002-5726-0255","contributorId":3120,"corporation":false,"usgs":true,"family":"George","given":"David","email":"dgeorge@usgs.gov","middleInitial":"L.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":880743,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rengers, Francis K. 0000-0002-1825-0943 frengers@usgs.gov","orcid":"https://orcid.org/0000-0002-1825-0943","contributorId":150422,"corporation":false,"usgs":true,"family":"Rengers","given":"Francis","email":"frengers@usgs.gov","middleInitial":"K.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":880744,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kean, Jason W. 0000-0003-3089-0369 jwkean@usgs.gov","orcid":"https://orcid.org/0000-0003-3089-0369","contributorId":1654,"corporation":false,"usgs":true,"family":"Kean","given":"Jason","email":"jwkean@usgs.gov","middleInitial":"W.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":880745,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70249515,"text":"70249515 - 2023 - Global methane emissions from rivers and streams","interactions":[],"lastModifiedDate":"2023-10-12T13:45:11.839911","indexId":"70249515","displayToPublicDate":"2023-08-16T08:43:02","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2840,"text":"Nature","active":true,"publicationSubtype":{"id":10}},"title":"Global methane emissions from rivers and streams","docAbstract":"<p><span>Methane (CH</span><sub>4</sub><span>) is a potent greenhouse gas and its concentrations have tripled in the atmosphere since the industrial revolution. There is evidence that global warming has increased CH</span><sub>4</sub><span>&nbsp;emissions from freshwater ecosystems</span><sup><a id=\"ref-link-section-d293024e611\" title=\"Yvon-Durocher, G. et al. Methane fluxes show consistent temperature dependence across microbial to ecosystem scales. Nature 507, 488–491 (2014).\" href=\"https://www.nature.com/articles/s41586-023-06344-6#ref-CR1\" data-track=\"click\" data-track-action=\"reference anchor\" data-track-label=\"link\" data-test=\"citation-ref\" aria-label=\"Reference 1\" data-mce-href=\"https://www.nature.com/articles/s41586-023-06344-6#ref-CR1\">1</a>,<a id=\"ref-link-section-d293024e614\" title=\"Zhu, Y. et al. Disproportionate increase in freshwater methane emissions induced by experimental warming. Nat. Clim. Change 10, 685–690 (2020).\" href=\"https://www.nature.com/articles/s41586-023-06344-6#ref-CR2\" data-track=\"click\" data-track-action=\"reference anchor\" data-track-label=\"link\" data-test=\"citation-ref\" aria-label=\"Reference 2\" data-mce-href=\"https://www.nature.com/articles/s41586-023-06344-6#ref-CR2\">2</a></sup><span>, providing positive feedback to the global climate. Yet for rivers and streams, the controls and the magnitude of CH</span><sub>4</sub><span>&nbsp;emissions remain highly uncertain</span><sup><a id=\"ref-link-section-d293024e620\" title=\"Stanley, E. H. et al. The ecology of methane in streams and rivers: patterns, controls, and global significance. Ecol. Monogr. 86, 146–171 (2016).\" href=\"https://www.nature.com/articles/s41586-023-06344-6#ref-CR3\" data-track=\"click\" data-track-action=\"reference anchor\" data-track-label=\"link\" data-test=\"citation-ref\" aria-label=\"Reference 3\" data-mce-href=\"https://www.nature.com/articles/s41586-023-06344-6#ref-CR3\">3</a>,<a id=\"ref-link-section-d293024e623\" title=\"Rosentreter, J. A. et al. Half of global methane emissions come from highly variable aquatic ecosystem sources. Nat. Geosci. 14, 225–230 (2021).\" href=\"https://www.nature.com/articles/s41586-023-06344-6#ref-CR4\" data-track=\"click\" data-track-action=\"reference anchor\" data-track-label=\"link\" data-test=\"citation-ref\" aria-label=\"Reference 4\" data-mce-href=\"https://www.nature.com/articles/s41586-023-06344-6#ref-CR4\">4</a></sup><span>. Here we report a spatially explicit global estimate of CH</span><sub>4</sub><span>&nbsp;emissions from running waters, accounting for 27.9 (16.7–39.7) Tg CH</span><sub>4</sub><span> per&nbsp;year and roughly equal in magnitude to those of other freshwater systems</span><sup><a id=\"ref-link-section-d293024e632\" title=\"Johnson, M. S. et al. Spatiotemporal methane emission from global reservoirs. J. Geophys. Res. Biogeosci. 126, e2021JG006305 (2021).\" href=\"https://www.nature.com/articles/s41586-023-06344-6#ref-CR5\" data-track=\"click\" data-track-action=\"reference anchor\" data-track-label=\"link\" data-test=\"citation-ref\" aria-label=\"Reference 5\" data-mce-href=\"https://www.nature.com/articles/s41586-023-06344-6#ref-CR5\">5</a>,<a id=\"ref-link-section-d293024e635\" title=\"Johnson, M. S., Matthews, E., Du, J., Genovese, V. &amp; Bastviken, D. Methane emission from global lakes: new spatiotemporal data and observation-driven modeling of methane dynamics indicates lower emissions. J. Geophys. Res. Biogeosci. 127, e2022JG006793 (2022).\" href=\"https://www.nature.com/articles/s41586-023-06344-6#ref-CR6\" data-track=\"click\" data-track-action=\"reference anchor\" data-track-label=\"link\" data-test=\"citation-ref\" aria-label=\"Reference 6\" data-mce-href=\"https://www.nature.com/articles/s41586-023-06344-6#ref-CR6\">6</a></sup><span>. Riverine CH</span><sub>4</sub><span>&nbsp;emissions are not strongly temperature dependent, with low average activation energy (</span><i>E</i><sub>M</sub><span> = 0.14 eV) compared with that of lakes and wetlands (</span><i>E</i><sub>M</sub><span> = 0.96 eV)</span><sup><a id=\"ref-link-section-d293024e650\" title=\"Yvon-Durocher, G. et al. Methane fluxes show consistent temperature dependence across microbial to ecosystem scales. Nature 507, 488–491 (2014).\" href=\"https://www.nature.com/articles/s41586-023-06344-6#ref-CR1\" data-track=\"click\" data-track-action=\"reference anchor\" data-track-label=\"link\" data-test=\"citation-ref\" aria-label=\"Reference 1\" data-mce-href=\"https://www.nature.com/articles/s41586-023-06344-6#ref-CR1\">1</a></sup><span>. By contrast, global patterns of emissions are characterized by large fluxes in high- and low-latitude settings as well as in human-dominated environments. These patterns are explained by edaphic and climate features that are linked to anoxia in and near fluvial habitats, including a high supply of organic matter and water saturation in hydrologically connected soils. Our results highlight the importance of land–water connections in regulating CH</span><sub>4</sub><span>&nbsp;supply to running waters, which is vulnerable not only to direct human modifications but also to several climate change responses on land.</span></p>","language":"English","publisher":"Nature Publications","doi":"10.1038/s41586-023-06344-6","usgsCitation":"Rocher-Ros, G., Stanley, E.H., Loken, L.C., Casson, N.J., Raymond, P.A., Liu, S., Amatulli, G., and Sponseller, R.A., 2023, Global methane emissions from rivers and streams: Nature, v. 621, p. 530-535, https://doi.org/10.1038/s41586-023-06344-6.","productDescription":"6 p.","startPage":"530","endPage":"535","ipdsId":"IP-146294","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":442410,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41586-023-06344-6","text":"Publisher Index Page"},{"id":421888,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"621","noUsgsAuthors":false,"publicationDate":"2023-08-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Rocher-Ros, Gerard","contributorId":329670,"corporation":false,"usgs":false,"family":"Rocher-Ros","given":"Gerard","email":"","affiliations":[{"id":12666,"text":"Swedish University of Agricultural Sciences","active":true,"usgs":false}],"preferred":false,"id":886050,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stanley, Emily H.","contributorId":55725,"corporation":false,"usgs":false,"family":"Stanley","given":"Emily","email":"","middleInitial":"H.","affiliations":[{"id":12951,"text":"Center for Limnology, University of Wisconsin Madison","active":true,"usgs":false}],"preferred":false,"id":886051,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Loken, Luke C. 0000-0003-3194-1498 lloken@usgs.gov","orcid":"https://orcid.org/0000-0003-3194-1498","contributorId":195600,"corporation":false,"usgs":true,"family":"Loken","given":"Luke","email":"lloken@usgs.gov","middleInitial":"C.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":886052,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Casson, Nora J.","contributorId":169271,"corporation":false,"usgs":false,"family":"Casson","given":"Nora","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":886053,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Raymond, Peter A.","contributorId":172876,"corporation":false,"usgs":false,"family":"Raymond","given":"Peter","email":"","middleInitial":"A.","affiliations":[{"id":17883,"text":"Yale School of Forestry and Environmental Studies, New Haven, CT","active":true,"usgs":false}],"preferred":false,"id":886054,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Liu, Shaoda","contributorId":257246,"corporation":false,"usgs":false,"family":"Liu","given":"Shaoda","email":"","affiliations":[{"id":51989,"text":"Yale School of Forestry and Environmental Studies, 195 Prospect Street, New Haven, CT, USA","active":true,"usgs":false}],"preferred":false,"id":886055,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Amatulli, Giuseppe","contributorId":330856,"corporation":false,"usgs":false,"family":"Amatulli","given":"Giuseppe","email":"","affiliations":[{"id":37550,"text":"Yale University","active":true,"usgs":false}],"preferred":false,"id":886056,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Sponseller, Ryan A.","contributorId":329667,"corporation":false,"usgs":false,"family":"Sponseller","given":"Ryan","email":"","middleInitial":"A.","affiliations":[{"id":24847,"text":"Umea University","active":true,"usgs":false}],"preferred":false,"id":886057,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70247900,"text":"70247900 - 2023 - A multi-ecosystem prioritization framework to balance competing habitat conservation needs of multiple species in decline","interactions":[],"lastModifiedDate":"2023-11-07T15:44:25.329372","indexId":"70247900","displayToPublicDate":"2023-08-16T06:37:20","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2602,"text":"Landscape Ecology","active":true,"publicationSubtype":{"id":10}},"title":"A multi-ecosystem prioritization framework to balance competing habitat conservation needs of multiple species in decline","docAbstract":"<h3 class=\"c-article__sub-heading\" data-test=\"abstract-sub-heading\">Context</h3><p>Individual species often drive habitat restoration action; however, management under this paradigm may negatively affect non-target species. Prioritization frameworks which explicitly consider benefits to target species while minimizing consequences for non-target species may improve management strategies and outcomes.</p><h3 class=\"c-article__sub-heading\" data-test=\"abstract-sub-heading\">Objectives</h3><p>We examined extents to which conifer removal, an approach frequently implemented to restore sagebrush ecosystems, can be conducted without detrimental effects to conifer-associated species, including the imperiled Pinyon Jay (<i>Gymnorhinus cyanocephalus</i>). Additionally, we prioritized sites for conifer removal, and predicted abundance responses for multiple species following simulated conifer removal at selected sites to achieve variable management objectives.</p><h3 class=\"c-article__sub-heading\" data-test=\"abstract-sub-heading\">Methods</h3><p>We used model-predicted changes in species’ densities following simulated conifer removal to identify optimal removal sites under single species, multi-species (ecosystem), and multi-ecosystem management scenarios. We simulated conifer removal at prioritized sites and evaluated resulting changes in abundance for six passerine species.</p><h3 class=\"c-article__sub-heading\" data-test=\"abstract-sub-heading\">Results</h3><p>Management prioritized for a single species (Brewer’s Sparrow) provided the greatest per-unit-effort benefits for that species but resulted in the lowest population outcomes for all other species considered. In comparison, prioritizations for multiple species within a single ecosystem (i.e., pinyon–juniper or sagebrush) resulted in larger population benefits for species associated with that ecosystem and reduced detrimental effects on non-target species associated with another ecosystem. For example, single species management for Brewer’s Sparrow resulted in an average increase of 1.38% for sagebrush-associated species and a 4.58% decrease for pinyon–juniper associated species. In contrast, when managing for multiple sagebrush-associated species sagebrush-associated songbird populations increased by 3.98% and pinyon–juniper associated species decreased by 2.36%, on average.</p><h3 class=\"c-article__sub-heading\" data-test=\"abstract-sub-heading\">Conclusions</h3><p>Our results illustrate single species management can result in detrimental outcomes and/or opportunity costs for non-target species compared to management designed to benefit multiple species. Our framework can be used to balance undesired consequences for non-target species and is adaptable for other systems and taxa.</p>","language":"English","publisher":"Springer","doi":"10.1007/s10980-023-01712-z","usgsCitation":"Van Lanen, N.J., Shyvers, J.E., Duchardt, C.J., and Aldridge, C.L., 2023, A multi-ecosystem prioritization framework to balance competing habitat conservation needs of multiple species in decline: Landscape Ecology, v. 38, p. 2795-2813, https://doi.org/10.1007/s10980-023-01712-z.","productDescription":"19 p.","startPage":"2795","endPage":"2813","ipdsId":"IP-147313","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":442419,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10980-023-01712-z","text":"Publisher Index Page"},{"id":435222,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9QFTK1D","text":"USGS data release","linkHelpText":"Prioritized sites for conifer removal within the Utah portion of Bird Conservation Region 16, 2020"},{"id":435221,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9MJHTMQ","text":"USGS data release","linkHelpText":"Predicted 2020 densities for 11 songbird species across the western United States"},{"id":420062,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"38","noUsgsAuthors":false,"publicationDate":"2023-08-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Van Lanen, Nicholas J. 0000-0003-0871-0261","orcid":"https://orcid.org/0000-0003-0871-0261","contributorId":302927,"corporation":false,"usgs":true,"family":"Van Lanen","given":"Nicholas","email":"","middleInitial":"J.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":880924,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shyvers, Jessica E. 0000-0002-4307-0004","orcid":"https://orcid.org/0000-0002-4307-0004","contributorId":288929,"corporation":false,"usgs":true,"family":"Shyvers","given":"Jessica","email":"","middleInitial":"E.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":880925,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Duchardt, Courtney J. 0000-0003-4563-0199","orcid":"https://orcid.org/0000-0003-4563-0199","contributorId":239754,"corporation":false,"usgs":false,"family":"Duchardt","given":"Courtney","middleInitial":"J.","affiliations":[{"id":48000,"text":"U Wyoming","active":true,"usgs":false}],"preferred":false,"id":880926,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Aldridge, Cameron L. 0000-0003-3926-6941 aldridgec@usgs.gov","orcid":"https://orcid.org/0000-0003-3926-6941","contributorId":191773,"corporation":false,"usgs":true,"family":"Aldridge","given":"Cameron","email":"aldridgec@usgs.gov","middleInitial":"L.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":880927,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70248714,"text":"70248714 - 2023 - A methodology to combine shaking and ground failure models for forecasting seismic damage to buried pipeline networks","interactions":[],"lastModifiedDate":"2023-12-04T17:17:34.591182","indexId":"70248714","displayToPublicDate":"2023-08-15T10:48:58","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"A methodology to combine shaking and ground failure models for forecasting seismic damage to buried pipeline networks","docAbstract":"<p><span>How does an earthquake affect buried pipeline networks? It is well known that the seismic performance of buried pipelines depends on ground failures (GFs) as well as strong ground shaking (SGS), but it is unclear how the various types of earthquake hazards should be collectively combined, as existing methodologies tend to examine each of the earthquake hazards separately. In this article, we develop a probability‐based methodology to consistently combine SGS with three types of GF (surface faulting, liquefaction, and landslide) for forecasting seismic damage in buried pipeline networks from a given earthquake rupture scenario. Using a gas transmission pipeline example, we illustrate how the proposed methodology enables others (e.g., researchers, pipeline operators who manage distribution lines, and consultants) to modularly combine various models such as those for estimating probability of GF, permanent ground displacements, and pipeline fragility. Finally, we compare the proposed methodology against the Hazus methodology to explore implications from considering each hazard one at a time.</span></p>","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120220132","usgsCitation":"Kwong, N.S., and Jaiswal, K.S., 2023, A methodology to combine shaking and ground failure models for forecasting seismic damage to buried pipeline networks: Bulletin of the Seismological Society of America, v. 113, no. 6, p. 2574-2595, https://doi.org/10.1785/0120220132.","productDescription":"22 p.","startPage":"2574","endPage":"2595","ipdsId":"IP-142244","costCenters":[{"id":78686,"text":"Geologic Hazards Science Center - Seismology / Geomagnetism","active":true,"usgs":true}],"links":[{"id":420906,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"113","issue":"6","noUsgsAuthors":false,"publicationDate":"2023-08-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Kwong, N. Simon 0000-0003-3017-9585","orcid":"https://orcid.org/0000-0003-3017-9585","contributorId":241863,"corporation":false,"usgs":true,"family":"Kwong","given":"N.","email":"","middleInitial":"Simon","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":883285,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jaiswal, Kishor S. 0000-0002-5803-8007 kjaiswal@usgs.gov","orcid":"https://orcid.org/0000-0002-5803-8007","contributorId":149796,"corporation":false,"usgs":true,"family":"Jaiswal","given":"Kishor","email":"kjaiswal@usgs.gov","middleInitial":"S.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":883286,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70247388,"text":"fs20233029 - 2023 - The 3D Elevation Program—Supporting Oregon's economy","interactions":[],"lastModifiedDate":"2023-08-22T15:10:07.494221","indexId":"fs20233029","displayToPublicDate":"2023-08-15T10:30:00","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-3029","displayTitle":"The 3D Elevation Program—Supporting Oregon’s Economy","title":"The 3D Elevation Program—Supporting Oregon's economy","docAbstract":"<h1>Introduction</h1><p>Oregon’s physical environments and vegetation are diverse. The varied geologic and climatic conditions combined with increasing population have created the need for high-quality elevation data that can be used for infrastructure management, forestry and wildfire management, agriculture, natural resources conservation, and other business uses. Critical applications that meet the State’s management needs depend on light detection and ranging (lidar) data that provide a highly detailed three-dimensional (3D) model of the Earth’s surface and aboveground features.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20233029","usgsCitation":"Carlson, T., 2023, The 3D Elevation Program—Supporting Oregon's economy: U.S. Geological Survey Fact Sheet 2023–3029, 2 p., https://doi.org/10.3133/fs20233029.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-122479","costCenters":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"links":[{"id":419966,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/fs/2023/3029/images/"},{"id":419965,"rank":4,"type":{"id":31,"text":"Publication 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 \"}}]}","contact":"<p>Director, <a href=\"https://www.usgs.gov/programs/national-geospatial-program\" data-mce-href=\"https://www.usgs.gov/programs/national-geospatial-program\">National Geospatial Program</a><br>U.S. Geological Survey<br>12201 Sunrise Valley Drive, Mail Stop 511<br>Reston, VA 20192</p><p>Email: <a href=\"mailto:3DEP@usgs.gov\" data-mce-href=\"mailto:3DEP@usgs.gov\">3DEP@usgs.gov</a></p>","tableOfContents":"<ul><li>Introduction</li><li>Infrastructure and Construction Management</li><li>Flood Risk Management</li><li>Wildfire Management, Planning, and Response</li><li>Geologic Resource Assessment and Hazard Mitigation</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2023-08-15","noUsgsAuthors":false,"publicationDate":"2023-08-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Carlson, Tom 0000-0002-5682-8988","orcid":"https://orcid.org/0000-0002-5682-8988","contributorId":304658,"corporation":false,"usgs":true,"family":"Carlson","given":"Tom","email":"","affiliations":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"preferred":true,"id":879423,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70247866,"text":"70247866 - 2023 - Modeling the effects of interior headland restoration on estuarine sediment transport processes in a marine-dominant estuary","interactions":[],"lastModifiedDate":"2025-05-15T13:14:24.695055","indexId":"70247866","displayToPublicDate":"2023-08-15T07:15:07","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3912,"text":"Frontiers in Marine Science","onlineIssn":"2296-7745","active":true,"publicationSubtype":{"id":10}},"title":"Modeling the effects of interior headland restoration on estuarine sediment transport processes in a marine-dominant estuary","docAbstract":"<p>The effects of interior headland restoration on estuarine sediment transport processes were assessed through process-based numerical modeling. Three proposed interior headland restoration scenarios in the Grand Bay estuary (Mississippi/Alabama) were modeled using Delft3D to understand impacts on suspended sediment concentrations, bed level morphology, and sediment fluxes under present-day conditions and a sea level rise (SLR) of 0.5 m, representing a high projection of SLR by the year 2050. Model results showed localized differences in bed levels near the restored features after a year of simulated morphologic change. The restored headland features acted as a sediment source to the immediate surroundings while also providing some non-significant sheltering effect of backshore shoals and marsh shorelines. Sediment fluxes were sensitive to wind directions and the presence of the restored headlands. However, regardless of wind direction, mean sea level, or restoration action, the greatest sediment fluxes were always export fluxes from the estuary, which were further increased with increased sea level. Suspended sediment concentrations were highly influenced by SLR in a non-linear manner. Sediment concentrations both increased and decreased depending on depth under SLR. Furthermore, SLR allowed for the suspension and deposition of sediments on the marsh platform. Overall, the influence of SLR was more impactful to changing sediment dynamics than the influence of the restoration features.</p>","language":"English","publisher":"Frontiers Media","doi":"10.3389/fmars.2023.1217830","usgsCitation":"Jenkins, R., Passeri, D., Smith, C., Thompson, D.M., and Smith, K., 2023, Modeling the effects of interior headland restoration on estuarine sediment transport processes in a marine-dominant estuary: Frontiers in Marine Science, v. 10, 1217830, 20 p.; Data Release, https://doi.org/10.3389/fmars.2023.1217830.","productDescription":"1217830, 20 p.; Data Release","ipdsId":"IP-153408","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":420007,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":435223,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P986ZR6B","text":"USGS data release","linkHelpText":"Modeling the Effects of Interior Headland Restoration on Estuarine Sediment Transport Processes in a Marine-Dominant Estuary: Delft3D Model Output"},{"id":442425,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"http://dx.doi.org/10.3389/fmars.2023.1217830","text":"Publisher Index Page"}],"country":"United States","state":"Alabama","otherGeospatial":"Grand Bay","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -88.42970223559698,\n              30.42582727404016\n            ],\n            [\n              -88.42970223559698,\n              30.33819705788089\n            ],\n            [\n              -88.27115514836353,\n              30.33819705788089\n            ],\n            [\n              -88.27115514836353,\n              30.42582727404016\n            ],\n            [\n              -88.42970223559698,\n              30.42582727404016\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"10","noUsgsAuthors":false,"publicationDate":"2023-08-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Jenkins, Robert L. III 0000-0003-2078-4618","orcid":"https://orcid.org/0000-0003-2078-4618","contributorId":202181,"corporation":false,"usgs":true,"family":"Jenkins","given":"Robert L.","suffix":"III","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":880792,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Passeri, Davina 0000-0002-9760-3195 dpasseri@usgs.gov","orcid":"https://orcid.org/0000-0002-9760-3195","contributorId":166889,"corporation":false,"usgs":true,"family":"Passeri","given":"Davina","email":"dpasseri@usgs.gov","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":880793,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Smith, Christopher G. 0000-0002-8075-4763","orcid":"https://orcid.org/0000-0002-8075-4763","contributorId":218439,"corporation":false,"usgs":true,"family":"Smith","given":"Christopher G.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":880794,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thompson, David M. 0000-0002-7103-5740 dthompson@usgs.gov","orcid":"https://orcid.org/0000-0002-7103-5740","contributorId":3502,"corporation":false,"usgs":true,"family":"Thompson","given":"David","email":"dthompson@usgs.gov","middleInitial":"M.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":880795,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Smith, Kathryn E.L. 0000-0002-7521-7875 kelsmith@usgs.gov","orcid":"https://orcid.org/0000-0002-7521-7875","contributorId":173264,"corporation":false,"usgs":true,"family":"Smith","given":"Kathryn","email":"kelsmith@usgs.gov","middleInitial":"E.L.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":880796,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70247706,"text":"sir20235067 - 2023 - Geology and assessment of coal resources for the Cherokee coal bed in the Fort Union Formation, south-central Wyoming","interactions":[],"lastModifiedDate":"2026-03-09T16:56:31.872382","indexId":"sir20235067","displayToPublicDate":"2023-08-14T17:00:00","publicationYear":"2023","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":"2023-5067","displayTitle":"Geology and Assessment of Coal Resources for the Cherokee Coal Bed in the Fort Union Formation, South-Central Wyoming","title":"Geology and assessment of coal resources for the Cherokee coal bed in the Fort Union Formation, south-central Wyoming","docAbstract":"<p>The Cherokee coal bed is a locally thick and laterally continuous coal bed in the Overland Member of the Paleocene Fort Union Formation in south-central Wyoming. It represents a significant resource that is easily accessible and may be extractable through both surface and underground mining methods. A database of more than 600 data points, comprising coalbed methane wells, coal exploration drill holes, and measured sections, was compiled from a previously released geologic database and reinterpreted to provide a more detailed geologic model for the Cherokee coal bed. The thickest part of the Cherokee coal bed lies along the crest of the Wamsutter arch, an east-west trending anticlinal feature that separates the Great Divide subbasin to north from the Washakie subbasin to the south. The Cherokee coal bed consists of several laterally persistent benches separated by partings that range in thickness from one inch to greater than 100 feet. A series of detailed geologic cross sections through the study area show both the structural geology and the distribution and areal extent of the individual coal benches of the Cherokee coal bed.</p><p>Data generated from the geologic model were used in stochastic geostatistical analyses to estimate the remaining or in-place coal resources. Certain parameters, as described later in the text, were applied to calculate available coal resources for surface and underground mining. This study is part of an ongoing process by the U.S. Geological Survey (USGS) to transition from a distance-based approach to a probabilistic approach for determining uncertainty in coal resource assessment. This probabilistic approach uses quantitative statistical methods to determine the potential range of uncertainty in coal resource estimates, whereas the distance-based approach does not provide any mathematical method to determine the range of uncertainty. Using stochastic geostatistical methods, utilizing 100 realizations or gridding iterations of the data, in-place resources were calculated, with a 90 percent probability, to be 15.261 ± 0.464 billion short tons (bst). Available coal resources tonnages were calculated using separate sets of criteria for surface and underground mining methods, based on probable mining parameters. Tonnage values were calculated based on estimated coal densities determined from available coal quality data. Available coal resources that meet the parameters for surface mining methods were calculated, with a 90 percent probability, to be 0.813 ± 0.038 bst.</p><p>Available coal resources that meet the parameters for underground mining methods were calculated, with a 90 percent probability, to be 2.393 ± 0.055 bst. The calculations were based on estimates of the resources that meet the parameters for the optimum mining of the thickest coal benches of the Cherokee coal bed. This is depicted in a series of cross sections through the study area that show projected underground mining horizons in the Cherokee coal bed, based on the thickest combinations of individual coal benches.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/sir20235067","programNote":"Energy Resources Program","usgsCitation":"Shaffer, B.N., and Olea, R.A., 2023, Geology and assessment of coal resources for the Cherokee coal bed in the Fort Union Formation, south-central Wyoming: U.S. Geological Survey Scientific Investigations Report 2023–5067, 29 p., https://doi.org/10.3133/sir20235067.","productDescription":"Report: vii, 30 p.; 6 Figures: 36.00 x 24.00 inches; Data Release","onlineOnly":"Y","ipdsId":"IP-132141","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":419765,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P92K1UT6","text":"USGS data release","linkHelpText":"Cherokee coal bed drill hole data from the Fort Union Formation in the Little Snake River coal field and Red Desert area, Wyoming"},{"id":419763,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5067/coverthb2.jpg"},{"id":419764,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5067/sir20235067.pdf","text":"Report","size":"6.73 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023-5067"},{"id":419766,"rank":4,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://pubs.usgs.gov/sir/2023/5067/sir20235067_fig07.pdf","text":"Figure 7","size":"108 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023-5067 Figure 7"},{"id":419768,"rank":6,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://pubs.usgs.gov/sir/2023/5067/sir20235067_fig09.pdf","text":"Figure 9","size":"104 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023-5067 Figure 9"},{"id":419769,"rank":7,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://pubs.usgs.gov/sir/2023/5067/sir20235067_fig16.pdf","text":"Figure 16","size":"96 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023-5067 Figure 16"},{"id":419770,"rank":8,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://pubs.usgs.gov/sir/2023/5067/sir20235067_fig17.pdf","text":"Figure 17","size":"104 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023-5067 Figure 17"},{"id":419771,"rank":9,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://pubs.usgs.gov/sir/2023/5067/sir20235067_fig18.pdf","text":"Figure 18","size":"104 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023-5067 Figure 18"},{"id":419767,"rank":5,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://pubs.usgs.gov/sir/2023/5067/sir20235067_fig08.pdf","text":"Figure 8","size":"104 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023-5067 Figure 8"},{"id":420209,"rank":10,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5067/images"},{"id":420210,"rank":11,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5067/sir20235067.xml"},{"id":420217,"rank":12,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20235067/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2023-5067"},{"id":500948,"rank":13,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115199.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Wyoming","otherGeospatial":"Cherokee Coal Bed, Fort Union Formation","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -108.3333,\n              42\n            ],\n            [\n              -108.3333,\n              41.4167\n            ],\n            [\n              -107.5,\n              41.4167\n            ],\n            [\n              -107.5,\n              42\n            ],\n            [\n              -108.3333,\n              42\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","contact":"<p>Director, <a href=\"https://www.usgs.gov/centers/central-energy-resources-science-center/\" data-mce-href=\"https://www.usgs.gov/centers/central-energy-resources-science-center/\">Central Energy Resources Science Center</a><br>U.S. Geological Survey<br>Box 25046, MS-939<br>Denver, CO 80225-0046</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Study Area</li><li>Geology</li><li>Data Sources </li><li>Cherokee Coal Bed Assessment </li><li>Surface Mining Methods</li><li>Underground Mining Methods </li><li>Results and Conclusions</li><li>References Cited</li></ul>","publishedDate":"2023-08-14","noUsgsAuthors":false,"publicationDate":"2023-08-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Shaffer, Brian N. 0000-0002-8787-7504","orcid":"https://orcid.org/0000-0002-8787-7504","contributorId":203755,"corporation":false,"usgs":true,"family":"Shaffer","given":"Brian N.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":880113,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Olea, Ricardo A. 0000-0003-4308-0808","orcid":"https://orcid.org/0000-0003-4308-0808","contributorId":224285,"corporation":false,"usgs":true,"family":"Olea","given":"Ricardo A.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":880114,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70246691,"text":"sir20235068 - 2023 - Flood-inundation maps for Fourmile Creek at Silver Grove, Kentucky","interactions":[],"lastModifiedDate":"2026-03-09T17:08:29.267739","indexId":"sir20235068","displayToPublicDate":"2023-08-14T09:50:00","publicationYear":"2023","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":"2023-5068","displayTitle":"Flood-Inundation Maps for Fourmile Creek at Silver Grove, Kentucky","title":"Flood-inundation maps for Fourmile Creek at Silver Grove, Kentucky","docAbstract":"<p>Digital flood-inundation maps for a 3.4-mile reach of Fourmile Creek at Silver Grove, Kentucky, were created by the U.S. Geological Survey (USGS) in cooperation with the City of Silver Grove and the U.S. Army Corps of Engineers Louisville District. Because the City of Silver Grove is subject to flooding from Fourmile Creek and the Ohio River (backwater flooding up Fourmile Creek), a set of flood-inundation maps was created, including maps for each flooding source considered independently and for possible scenarios involving flooding from both sources combined. The flood-inundation maps depict estimates of the areal extent and depth of flooding corresponding to a range of gage heights (gage height is commonly referred to as “stage,” or the water-surface elevation at a streamgage) at the USGS streamgage on Fourmile Creek at Grays Crossing at Silver Grove, Ky. (station number 03238785), and the USGS streamgage on Fourmile Creek at Highway 8 at Silver Grove, Ky. (station number 03238798). Near-real-time stages at these streamgages can be obtained from the USGS National Water Information System at <a href=\"https://waterdata.usgs.gov/\" data-mce-href=\"https://waterdata.usgs.gov/\">https://waterdata.usgs.gov/</a>. The USGS streamgage on the Ohio River at Cincinnati, Ohio (station number 03255000), is also important in this study because the National Weather Service (NWS) Advanced Hydrologic Prediction Service (AHPS; <a href=\"https://water.weather.gov/ahps/\" data-mce-href=\"https://water.weather.gov/ahps/\">https://water.weather.gov/ahps/</a>) forecasts flood hydrographs for this site (NWS AHPS site CCNO1). The peak-stage information forecast by the NWS AHPS can be used in conjunction with the maps developed in this study to show predicted areas of flood inundation.</p><p>Flood profiles were computed for the Fourmile Creek study reach by means of a one-dimensional, step-backwater hydraulic model (HEC-RAS) developed by the U.S. Army Corps of Engineers. The hydraulic model was calibrated by using the current stage-discharge relation (USGS rating number 1.1) at USGS streamgage 03238785, Fourmile Creek at Grays Crossing at Silver Grove, Ky. The model was then used to compute water-surface profiles for 83 combinations of flood stages on the Ohio River and Fourmile Creek ranging from approximately base flow to greater than a 2-percent annual exceedance probability flood in the model reach. An additional 50 water-surface profiles were computed for backwater-only flooding (from the Ohio River) for flood elevations (referenced to the North American Vertical Datum of 1988 [NAVD 88]) at 1-foot intervals referenced to USGS streamgage 03238798, Fourmile Creek at Highway 8 at Silver Grove, Ky.; these elevations ranged from approximately normal pool (460 ft, NAVD 88) to approximately a 0.2-percent annual exceedance probability flood (509 ft, NAVD 88) on the Ohio River. The computed water-surface profile information was then combined with a digital elevation model derived from light detection and ranging (lidar) data to delineate the approximate flooded areas.</p><p>The digital flood-inundation maps are available through the USGS Flood Inundation Mapper application (<a href=\"https://fim.wim.usgs.gov/fim/\" data-mce-href=\"https://fim.wim.usgs.gov/fim/\">https://fim.wim.usgs.gov/fim/</a>), which presents map libraries and provides detailed information on flood extent and depths for selected sites. The flood-inundation maps developed in this study, in conjunction with the real-time stage data from the USGS streamgages on Fourmile Creek at Silver Grove, Ky., and forecasted stream stages from the NWS AHPS, are intended to provide information that can help inform the public about potential flooding and provide emergency management personnel with a tool to efficiently manage emergency flood operations, such as evacuations and road closures, and assist in postflood recovery efforts.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235068","collaboration":"Prepared in cooperation with the City of Silver Grove and the U.S. Army Corps of Engineers Louisville District","usgsCitation":"Boldt, J.A., 2023, Flood-inundation maps for Fourmile Creek at Silver Grove, Kentucky: U.S. Geological Survey Scientific Investigations Report 2023–5068, 22 p., https://doi.org/10.3133/sir20235068.","productDescription":"Report: vii, 22 p.; Data Release","numberOfPages":"22","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-130251","costCenters":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":500949,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115179.htm","linkFileType":{"id":5,"text":"html"}},{"id":418995,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9VJSH7D","text":"USGS data release","linkHelpText":"Geospatial datasets and model for the flood-inundation study of Fourmile Creek at Silver Grove, Kentucky"},{"id":418994,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5068/sir20235068.XML"},{"id":418993,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5068/images/"},{"id":418992,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20235068/full","text":"Report","description":"SIR 2023-5068"},{"id":418991,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5068/sir20235068.pdf","text":"Report","size":"5.38 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023-5068"},{"id":418990,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5068/coverthb.jpg"}],"country":"United States","state":"Kentucky","city":"Silver Grove","otherGeospatial":"Fourmile Creek","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -84.5333,\n              39.1333\n            ],\n            [\n              -84.5333,\n              39.0167\n            ],\n            [\n              -84.3583,\n              39.0167\n            ],\n            [\n              -84.3583,\n              39.1333\n            ],\n            [\n              -84.5333,\n              39.1333\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","contact":"<p>Director, <a href=\"https://www.usgs.gov/centers/oki-water\" data-mce-href=\"https://www.usgs.gov/centers/oki-water\">Ohio-Kentucky-Indiana Water Science Center</a><br>U.S. Geological Survey<br>5957 Lakeside Blvd.<br>Indianapolis, IN 46278-1996</p><p><a href=\"https://pubs.er.usgs.gov/contact\" data-mce-href=\"../contact\">Contact Pubs Warehouse</a></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><li>Appendix 1. Supplemental Photographs</li><li>Appendix 2. Modeled Combinations of Ohio River Elevation and Fourmile Creek Stage at Grays Crossing, Silver Grove, Kentucky</li></ul>","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"publishedDate":"2023-08-14","noUsgsAuthors":false,"publicationDate":"2023-08-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Boldt, Justin A. 0000-0002-0771-3658","orcid":"https://orcid.org/0000-0002-0771-3658","contributorId":207849,"corporation":false,"usgs":true,"family":"Boldt","given":"Justin","email":"","middleInitial":"A.","affiliations":[{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true},{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true},{"id":27231,"text":"Indiana-Kentucky Water Science Center","active":true,"usgs":true}],"preferred":true,"id":877994,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70247673,"text":"ofr20231057 - 2023 - Drought-vulnerability assessment of public water systems in West Virginia","interactions":[],"lastModifiedDate":"2026-02-11T21:30:53.996113","indexId":"ofr20231057","displayToPublicDate":"2023-08-14T07:23:42","publicationYear":"2023","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":"2023-1057","displayTitle":"Drought-Vulnerability Assessment of Public Water Systems in West Virginia","title":"Drought-vulnerability assessment of public water systems in West Virginia","docAbstract":"<p>Water withdrawn from rivers and streams accounts for approximately 80 percent of the public water supply in West Virginia. Localized and (or) seasonal droughts may threaten future water availability in the state, particularly in rural communities located in the headwaters of unregulated watersheds. Monthly water withdrawal data obtained from the West Virginia Department of Environmental Protection’s Large Quantity User program’s regulatory database was used to calculate all-time, seasonal, and monthly 75th quantile withdrawal rates for 109 public water system (PWS) intakes withdrawing from surface waters in West Virginia. A drought-vulnerability assessment value was calculated by comparing PWS withdrawal rates to the 1-day, 10-year hydrologically based streamflow statistic (1Q10) for 71 of the 109 PWS in locations with valid streamflow statistics. Withdrawal rates were evaluated against thresholds representing different levels of drought-related impacts from the West Virginia interagency drought plan and ecological-flow literature. The drought-vulnerability assessment found 33 of 71 PWS have 75th quantile withdrawal rates greater than 100 percent of 1Q10 streamflow. Forty-five of 71 PWS have 75th quantile withdrawal rates more than 10 percent of 1Q10 streamflow, suggesting some level of ecological impairment during severe drought. Additionally, a publicly available, near real-time drought-awareness web tool was created to compare the estimated withdrawal rate for 109 PWS to forecast streamflows from the National Water Model to support decision-making for emergency and water managers.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231057","usgsCitation":"Kearns, M.R., Faunce, K.E., and Messinger, T., 2023, Drought-vulnerability assessment of public water systems in West Virginia: U.S. Geological Survey Open-File Report 2023–1057, 14 p., https://doi.org/10.3133/ofr20231057.","productDescription":"Report: viii, 14 p.; Data Release","numberOfPages":"14","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-151563","costCenters":[{"id":37280,"text":"Virginia and West Virginia Water Science Center ","active":true,"usgs":true}],"links":[{"id":420078,"rank":6,"type":{"id":30,"text":"Data 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Virginia\",\"nation\":\"USA  \"}}]}","contact":"<p>Director, <a href=\"virginia-and-west-virginia-water-science-center\" data-mce-href=\"virginia-and-west-virginia-water-science-center\">Virginia and West Virginia Water Science Center</a><br>U.S. Geological Survey<br>1730 East Parham Road<br>Richmond, VA 23228</p><p><a href=\"https://pubs.er.usgs.gov/contact\" data-mce-href=\"../contact\">Contact Pubs Warehouse</a></p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Study Methods</li><li>Discussion of Drought-Vulnerability Assessment</li><li>Summary</li><li>References Cited</li><li>Appendix 1. Seasonal Variation in Drought-Vulnerability Assessment of Public Water Systems in West Virginia</li></ul>","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2023-08-18","noUsgsAuthors":false,"publicationDate":"2023-08-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Kearns, Matthew R. 0000-0002-7338-5146","orcid":"https://orcid.org/0000-0002-7338-5146","contributorId":288957,"corporation":false,"usgs":true,"family":"Kearns","given":"Matthew","email":"","middleInitial":"R.","affiliations":[{"id":37280,"text":"Virginia and West Virginia Water Science Center ","active":true,"usgs":true}],"preferred":true,"id":880000,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Faunce, Kaycee E. 0000-0002-9178-0692","orcid":"https://orcid.org/0000-0002-9178-0692","contributorId":224488,"corporation":false,"usgs":true,"family":"Faunce","given":"Kaycee","email":"","middleInitial":"E.","affiliations":[{"id":37759,"text":"VA/WV Water Science Center","active":true,"usgs":true}],"preferred":true,"id":880001,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Messinger, Terence 0000-0003-4084-9298 tmessing@usgs.gov","orcid":"https://orcid.org/0000-0003-4084-9298","contributorId":2717,"corporation":false,"usgs":true,"family":"Messinger","given":"Terence","email":"tmessing@usgs.gov","affiliations":[{"id":642,"text":"West Virginia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":880002,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70250426,"text":"70250426 - 2023 - Predicting burn severity for integration with post-fire debris-flow hazard assessment: A case study from the Upper Colorado River Basin, USA","interactions":[],"lastModifiedDate":"2023-12-11T11:44:48.711129","indexId":"70250426","displayToPublicDate":"2023-08-14T06:47:57","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2083,"text":"International Journal of Wildland Fire","active":true,"publicationSubtype":{"id":10}},"title":"Predicting burn severity for integration with post-fire debris-flow hazard assessment: A case study from the Upper Colorado River Basin, USA","docAbstract":"<p><strong>Background:<span>&nbsp;</span></strong>Burn severity significantly increases the likelihood and volume of post-wildfire debris flows. Pre-fire severity predictions can expedite mitigation efforts because precipitation contributing to these hazards often occurs shortly after wildfires, leaving little time for post-fire planning and management.</p><p><strong>Aim:<span>&nbsp;</span></strong>The aim of this study was to predict burn severity using pre-fire conditions of individual wildfire events and estimate potential post-fire debris flow to unburned areas.</p><p><strong>Methods:<span>&nbsp;</span></strong>We used random forests to model dNBR from pre-fire weather, fuels, topography, and remotely sensed data. We validated our model predictions against post-fire observations and potential post-fire debris-flow hazard estimates.</p><p><strong>Key results:<span>&nbsp;</span></strong>Fuels, pre-fire weather, and topography were important predictors of burn severity, although predictor importance varied between fires. Post-fire debris-flow hazard rankings from predicted burn severity (pre-fire) were similar to hazard assessments based on observed burn severity (post-fire).</p><p><strong>Conclusion:<span>&nbsp;</span></strong>Predicted burn severity can serve as an input to post-fire debris-flow models before wildfires occur, antecedent to standard post-fire burn severity products. Assessing a larger set of fires under disparate conditions and landscapes will be needed to refine predictive models.</p><p><strong>Implications:<span>&nbsp;</span></strong>Burn severity models based on pre-fire conditions enable the prediction of fire effects and identification of potential hazards to prioritise response and mitigation.</p>","language":"English","publisher":"CSIRO Publishing","doi":"10.1071/WF22200","usgsCitation":"Wells, A.G., Hawbaker, T., Hiers, J.K., Kean, J.W., Loehman, R.A., and Steblein, P.F., 2023, Predicting burn severity for integration with post-fire debris-flow hazard assessment: A case study from the Upper Colorado River Basin, USA: International Journal of Wildland Fire, v. 32, no. 9, p. 1315-1331, https://doi.org/10.1071/WF22200.","productDescription":"17 p.","startPage":"1315","endPage":"1331","ipdsId":"IP-139674","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":442431,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1071/wf22200","text":"Publisher Index Page"},{"id":423322,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, Colorado, New Mexico, Utah, Wyoming","otherGeospatial":"Colorado River Basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -111.06565163962557,\n              43.427546253490476\n            ],\n            [\n              -110.98798557839956,\n              42.01861589248239\n            ],\n            [\n              -111.167880059579,\n              41.798766051959774\n            ],\n            [\n              -111.44306126894347,\n              39.908461537613874\n            ],\n            [\n              -112.53658323354853,\n              37.68116371252778\n            ],\n            [\n              -111.48694518463799,\n              36.98448253816319\n            ],\n            [\n              -108.9707627610722,\n              35.73546875520603\n            ],\n            [\n              -106.21544190659625,\n              35.95406463803488\n            ],\n            [\n              -105.24197446984596,\n              37.061352239951816\n            ],\n            [\n              -105.22957281158256,\n              38.778571358020145\n            ],\n            [\n              -105.72213937268728,\n              40.11156263554764\n            ],\n            [\n              -106.36800305274357,\n              41.14373257717733\n            ],\n            [\n              -108.44088579766407,\n              42.693595341045835\n            ],\n            [\n              -109.65640871320971,\n              43.49287890884281\n            ],\n            [\n              -111.06565163962557,\n              43.427546253490476\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"32","issue":"9","noUsgsAuthors":false,"publicationDate":"2023-08-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Wells, Adam Gerhard 0000-0001-9675-4963","orcid":"https://orcid.org/0000-0001-9675-4963","contributorId":270137,"corporation":false,"usgs":true,"family":"Wells","given":"Adam","email":"","middleInitial":"Gerhard","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":889876,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hawbaker, Todd 0000-0003-0930-9154 tjhawbaker@usgs.gov","orcid":"https://orcid.org/0000-0003-0930-9154","contributorId":568,"corporation":false,"usgs":true,"family":"Hawbaker","given":"Todd","email":"tjhawbaker@usgs.gov","affiliations":[{"id":547,"text":"Rocky Mountain Geographic Science Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":889877,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hiers, John Kevin 0000-0002-6813-8941","orcid":"https://orcid.org/0000-0002-6813-8941","contributorId":332282,"corporation":false,"usgs":true,"family":"Hiers","given":"John","email":"","middleInitial":"Kevin","affiliations":[{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true}],"preferred":true,"id":889878,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kean, Jason W. 0000-0003-3089-0369 jwkean@usgs.gov","orcid":"https://orcid.org/0000-0003-3089-0369","contributorId":1654,"corporation":false,"usgs":true,"family":"Kean","given":"Jason","email":"jwkean@usgs.gov","middleInitial":"W.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":889879,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Loehman, Rachel A. 0000-0001-7680-1865 rloehman@usgs.gov","orcid":"https://orcid.org/0000-0001-7680-1865","contributorId":187605,"corporation":false,"usgs":true,"family":"Loehman","given":"Rachel","email":"rloehman@usgs.gov","middleInitial":"A.","affiliations":[{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":false,"id":889880,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Steblein, Paul F. 0000-0001-7856-5106","orcid":"https://orcid.org/0000-0001-7856-5106","contributorId":213237,"corporation":false,"usgs":true,"family":"Steblein","given":"Paul","email":"","middleInitial":"F.","affiliations":[{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true}],"preferred":true,"id":889881,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70256607,"text":"70256607 - 2023 - Conservation at the nexus of niches: Multidimensional niche modeling to improve management of Prairie Chub","interactions":[],"lastModifiedDate":"2024-08-26T15:28:07.371737","indexId":"70256607","displayToPublicDate":"2023-08-11T10:19:49","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"title":"Conservation at the nexus of niches: Multidimensional niche modeling to improve management of Prairie Chub","docAbstract":"<h3 id=\"nafm10860-sec-0100-title\" class=\"article-section__sub-title section1\">Objective</h3><p>A central challenge in applied ecology is understanding how organisms are spatially and temporally distributed and how management might be tailored to maintain or restore species distributions. The niche concept is central to understanding species distributions, but the diversity of niche definitions requires that multiple dimensions be considered. For example, the Grinnellian niche concept focuses on environmental conditions that allow species to persist, the Eltonian niche concept stresses the influence of biotic interactions, and the fundamental niche concept considers both abiotic and biotic environmental features to define spaces that organisms could occupy.</p><h3 id=\"nafm10860-sec-0200-title\" class=\"article-section__sub-title section1\">Methods</h3><p>We combined abiotic (<i>A</i>), biotic (<i>B</i>), and movement (<i>M</i>) information (collectively, BAM model) to map the multidimensional niche of Prairie Chub<span>&nbsp;</span><i>Macrhybopsis australis</i>, a regionally endemic freshwater fish currently under review for listing under the Endangered Species Act. We estimated<span>&nbsp;</span><i>A</i><span>&nbsp;</span>using remotely sensed environmental riverscape variables,<span>&nbsp;</span><i>B</i><span>&nbsp;</span>using the spatial distribution of a hybridization zone between Prairie Chub and Shoal Chub<span>&nbsp;</span><i>M. hyostoma</i>, and<span>&nbsp;</span><i>M</i><span>&nbsp;</span>using data from a mark–recapture study.</p><h3 id=\"nafm10860-sec-0300-title\" class=\"article-section__sub-title section1\">Result</h3><p>The BAM model estimated the spatial extent of multiple niches, including the Grinnellian (<i>A</i>; extent = 944 km of river), Eltonian (<i>B</i>; 2974 km), and fundamental niche (overlap of<span>&nbsp;</span><i>A</i> + <i>B</i>; 645 km) niches. When<span>&nbsp;</span><i>A</i>,<span>&nbsp;</span><i>B</i>, and<span>&nbsp;</span><i>M</i><span>&nbsp;</span>components were combined, the estimated extent of the Prairie Chub niche was 645 km.</p><h3 id=\"nafm10860-sec-0800-title\" class=\"article-section__sub-title section1\">Conclusion</h3><p>Our work shows that the realized, multidimensional niche of Prairie Chub includes medium to large rivers with high habitat connectivity in the upper–middle Red River basin upstream of the distribution of Shoal Chub. The current Prairie Chub distribution could be maintained by preventing further habitat fragmentation and maintaining the environmental gradient separating Prairie Chub from Shoal Chub. Expansion of the species distribution may be possible through restoration of longitudinal fluvial connectivity.</p>","language":"English","publisher":"American Fisheries Society","doi":"10.1002/nafm.10860","usgsCitation":"Steffensmeier, Z.D., Brewer, S.K., Wedgeworth, M., Starks, T.A., Rodger, A.W., Nguyen, E., and Perkin, J., 2023, Conservation at the nexus of niches: Multidimensional niche modeling to improve management of Prairie Chub: North American Journal of Fisheries Management, v. 43, no. 5, p. 1205-1224, https://doi.org/10.1002/nafm.10860.","productDescription":"20 p.","startPage":"1205","endPage":"1224","ipdsId":"IP-142909","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":433158,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"43","issue":"5","noUsgsAuthors":false,"publicationDate":"2023-08-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Steffensmeier, Zachary D.","contributorId":341344,"corporation":false,"usgs":false,"family":"Steffensmeier","given":"Zachary","email":"","middleInitial":"D.","affiliations":[{"id":6747,"text":"Texas A&M University","active":true,"usgs":false}],"preferred":false,"id":908270,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brewer, Shannon K. 0000-0002-1537-3921 skbrewer@usgs.gov","orcid":"https://orcid.org/0000-0002-1537-3921","contributorId":2252,"corporation":false,"usgs":true,"family":"Brewer","given":"Shannon","email":"skbrewer@usgs.gov","middleInitial":"K.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":908271,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wedgeworth, Maeghen","contributorId":341345,"corporation":false,"usgs":false,"family":"Wedgeworth","given":"Maeghen","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":908272,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Starks, Trevor A.","contributorId":145640,"corporation":false,"usgs":false,"family":"Starks","given":"Trevor","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":908273,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rodger, Anthony W.","contributorId":302586,"corporation":false,"usgs":false,"family":"Rodger","given":"Anthony","email":"","middleInitial":"W.","affiliations":[{"id":27443,"text":"Oklahoma Department of Wildlife Conservation","active":true,"usgs":false}],"preferred":false,"id":908274,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Nguyen, Erin","contributorId":341346,"corporation":false,"usgs":false,"family":"Nguyen","given":"Erin","email":"","affiliations":[{"id":6747,"text":"Texas A&M University","active":true,"usgs":false}],"preferred":false,"id":908275,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Perkin, Joshuah S.","contributorId":238286,"corporation":false,"usgs":false,"family":"Perkin","given":"Joshuah S.","affiliations":[{"id":47708,"text":"Department of Wildlife and Fisheries Sciences, Texas A&M University, College Station, TX","active":true,"usgs":false}],"preferred":false,"id":908276,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
]}