{"pageNumber":"115","pageRowStart":"2850","pageSize":"25","recordCount":40783,"records":[{"id":70247122,"text":"70247122 - 2023 - Debris-flow process controls on steepland morphology in the San Gabriel Mountains, California","interactions":[],"lastModifiedDate":"2023-07-25T14:13:55.913304","indexId":"70247122","displayToPublicDate":"2023-07-14T09:07:49","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7357,"text":"JGR Earth Surface","active":true,"publicationSubtype":{"id":10}},"title":"Debris-flow process controls on steepland morphology in the San Gabriel Mountains, California","docAbstract":"<p><span>Steep landscapes evolve largely by debris flows, in addition to fluvial and hillslope processes. Abundant field observations document that debris flows incise valley bottoms and transport substantial sediment volumes, yet their contributions to steepland morphology remain uncertain. This has, in turn, limited the development of debris-flow incision rate formulations that produce morphology consistent with natural landscapes. In many landscapes, including the San Gabriel Mountains (SGM), California, steady-state fluvial channel longitudinal profiles are concave-up and exhibit a power-law relationship between channel slope and drainage area. At low drainage areas, however, valley slopes become nearly constant. These topographic forms result in a characteristically curved slope-area signature in log-log space. Here, we use a one-dimensional landform evolution model that incorporates debris-flow erosion to reproduce the relationship between this curved slope-area signature and erosion rate in the SGM. Topographic analysis indicates that the drainage area at which steepland valleys transition to fluvial channels correlates with measured erosion rates in the SGM, and our model results reproduce these relationships. Further, the model only produces realistic valley profiles when parameters that dictate the relationship between debris-flow erosion, valley-bottom slope, and debris-flow depth are within a narrow range. This result helps place constraints on the mathematical form of a debris-flow incision law. Finally, modeled fluvial incision outpaces debris-flow erosion at drainage areas less than those at which valleys morphologically transition from near-invariant slopes to concave profiles. This result emphasizes the critical role of debris-flow incision for setting steepland form, even as fluvial incision becomes the dominant incisional process.</span></p>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2022JF007017","usgsCitation":"Struble, W., McGuire, L.A., McCoy, S., Barnhart, K.R., and Marc, O., 2023, Debris-flow process controls on steepland morphology in the San Gabriel Mountains, California: JGR Earth Surface, v. 128, no. 7, e2022JF007017, 29 p., https://doi.org/10.1029/2022JF007017.","productDescription":"e2022JF007017, 29 p.","ipdsId":"IP-147440","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":442759,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2022jf007017","text":"Publisher Index Page"},{"id":419301,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Gabriel Mountains","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -118.01260424279738,\n              34.14566760098988\n            ],\n            [\n              -117.67000792883225,\n              34.147752407886856\n            ],\n            [\n              -117.3853506973756,\n              34.19777233450243\n            ],\n            [\n              -117.11076982809459,\n              34.09144456704166\n            ],\n            [\n              -116.9344334900242,\n              33.94110717551865\n            ],\n            [\n              -116.67244800052214,\n              33.974538472354965\n            ],\n            [\n              -116.69511981541675,\n              34.30812790101858\n            ],\n            [\n              -117.29718245539995,\n              34.32893347252433\n            ],\n            [\n              -117.75313784383901,\n              34.445349311566275\n            ],\n            [\n              -118.02268053203237,\n              34.51387565376443\n            ],\n            [\n              -118.46855955829582,\n              34.40586922676006\n            ],\n            [\n              -118.51390318808532,\n              34.34141433967626\n            ],\n            [\n              -118.01260424279738,\n              34.14566760098988\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"128","issue":"7","noUsgsAuthors":false,"publicationDate":"2023-07-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Struble, William 0000-0002-8163-5088","orcid":"https://orcid.org/0000-0002-8163-5088","contributorId":241913,"corporation":false,"usgs":false,"family":"Struble","given":"William","email":"","affiliations":[{"id":6604,"text":"University of Oregon","active":true,"usgs":false}],"preferred":false,"id":878951,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McGuire, Luke A. 0000-0001-8178-7922 lmcguire@usgs.gov","orcid":"https://orcid.org/0000-0001-8178-7922","contributorId":203420,"corporation":false,"usgs":false,"family":"McGuire","given":"Luke","email":"lmcguire@usgs.gov","middleInitial":"A.","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":878952,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McCoy, Scott W.","contributorId":267182,"corporation":false,"usgs":false,"family":"McCoy","given":"Scott W.","affiliations":[{"id":16686,"text":"University of Nevada, Reno","active":true,"usgs":false}],"preferred":false,"id":878953,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"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":878954,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Marc, Odin","contributorId":198732,"corporation":false,"usgs":false,"family":"Marc","given":"Odin","email":"","affiliations":[],"preferred":false,"id":878955,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70246768,"text":"70246768 - 2023 - Prioritizing the risk and management of introduced species in a landscape with high indigenous biodiversity","interactions":[],"lastModifiedDate":"2023-07-19T13:54:11.562487","indexId":"70246768","displayToPublicDate":"2023-07-14T08:52:22","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1092,"text":"Bulletin, Southern California Academy of Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Prioritizing the risk and management of introduced species in a landscape with high indigenous biodiversity","docAbstract":"<p><span>Risk analysis protocols for prioritizing the management of non-native species are numerous, yet few incorporate risk and management in the same analysis or accommodate a broad diversity of taxa outside of a specific geographic area. We adapted a protocol that accounts for these factors to address non-native animal species in the Southern California/Northern Baja California Coast Ecoregion near the international border in San Diego County, an area with high indigenous biodiversity and high numbers of species of conservation concern. This stepwise, semi-quantitative protocol is applicable to any animal group in any predefined geographic area, relies on consensus-building among taxonomic experts, and has been vetted through previous use and in peer-reviewed literature. Our results show that the final prioritization was driven mainly by management feasibility, with top-ranked species having multitrophic effects that favor other non-native invaders over native residents. Conditions within the assessment area required some modification to the protocol as it was originally designed, namely a shift in emphasis from eradication to control, given that eradication is implausible for most non-native species in the assessment area. We call attention to taxon-specific issues that surfaced during the analysis, identify areas for improvement in this first-ever risk assessment for invasive animal species in the Natural Communities Conservation Plan/Habitat Conservation Plan (NCCP/HCP) reserve system of San Diego County, and provide suggestions for further refinement of the protocol. This study builds on the effort to standardize risk analysis for invasive species globally, given that many of the same invaders present threats to indigenous biodiversity worldwide.</span></p>","language":"English","publisher":"Southern California Academy of Sciences","doi":"10.3160/0038-3872-122.2.101","usgsCitation":"Richmond, J.Q., Kingston, J., Ewing, B., Bear, W.M., Hathaway, S.A., Lee, C., Swift, C.C., Preston, K.L., Schultz, A.J., Kus, B., Russell, K., Unitt, P., Hollingsworth, B.D., Espinoza, R.E., Wall, M., Tremor, S., Palenscar, K., and Fisher, R., 2023, Prioritizing the risk and management of introduced species in a landscape with high indigenous biodiversity: Bulletin, Southern California Academy of Sciences, v. 122, no. 2, p. 101-121, https://doi.org/10.3160/0038-3872-122.2.101.","productDescription":"21 p.","startPage":"101","endPage":"121","ipdsId":"IP-152994","costCenters":[{"id":651,"text":"Western Ecological Research 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Jonathan Q. 0000-0001-9398-4894 jrichmond@usgs.gov","orcid":"https://orcid.org/0000-0001-9398-4894","contributorId":5400,"corporation":false,"usgs":true,"family":"Richmond","given":"Jonathan","email":"jrichmond@usgs.gov","middleInitial":"Q.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":878234,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kingston, Jennifer 0000-0002-9994-1972","orcid":"https://orcid.org/0000-0002-9994-1972","contributorId":258244,"corporation":false,"usgs":true,"family":"Kingston","given":"Jennifer","email":"","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":878235,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ewing, Brittany 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0000-0002-4167-8059","orcid":"https://orcid.org/0000-0002-4167-8059","contributorId":206793,"corporation":false,"usgs":true,"family":"Hathaway","given":"Stacie","email":"","middleInitial":"A.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":878238,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lee, Cedric","contributorId":316748,"corporation":false,"usgs":false,"family":"Lee","given":"Cedric","email":"","affiliations":[{"id":12725,"text":"Natural History Museum of Los Angeles County","active":true,"usgs":false}],"preferred":false,"id":878239,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Swift, Camm C.","contributorId":139395,"corporation":false,"usgs":false,"family":"Swift","given":"Camm","email":"","middleInitial":"C.","affiliations":[{"id":12725,"text":"Natural History Museum of Los Angeles County","active":true,"usgs":false}],"preferred":false,"id":878240,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Preston, Kristine L. 0000-0002-6958-1128 kpreston@usgs.gov","orcid":"https://orcid.org/0000-0002-6958-1128","contributorId":207765,"corporation":false,"usgs":true,"family":"Preston","given":"Kristine","email":"kpreston@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":878241,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Schultz, Allison J.","contributorId":316750,"corporation":false,"usgs":false,"family":"Schultz","given":"Allison","email":"","middleInitial":"J.","affiliations":[{"id":12725,"text":"Natural History Museum of Los Angeles County","active":true,"usgs":false}],"preferred":false,"id":878242,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Kus, Barbara E. 0000-0002-3679-3044 barbara_kus@usgs.gov","orcid":"https://orcid.org/0000-0002-3679-3044","contributorId":3026,"corporation":false,"usgs":true,"family":"Kus","given":"Barbara E.","email":"barbara_kus@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":878243,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Russell, Kerwin","contributorId":297133,"corporation":false,"usgs":false,"family":"Russell","given":"Kerwin","email":"","affiliations":[{"id":64299,"text":"Riverside-Corona Resource Conservation District","active":true,"usgs":false}],"preferred":false,"id":878244,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Unitt, Philip","contributorId":316753,"corporation":false,"usgs":false,"family":"Unitt","given":"Philip","affiliations":[{"id":16175,"text":"San Diego Natural History Museum","active":true,"usgs":false}],"preferred":false,"id":878245,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Hollingsworth, Bradford D.","contributorId":316755,"corporation":false,"usgs":false,"family":"Hollingsworth","given":"Bradford","email":"","middleInitial":"D.","affiliations":[{"id":16175,"text":"San Diego Natural History Museum","active":true,"usgs":false}],"preferred":false,"id":878246,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Espinoza, Robert E.","contributorId":316757,"corporation":false,"usgs":false,"family":"Espinoza","given":"Robert","email":"","middleInitial":"E.","affiliations":[{"id":39477,"text":"California State University Northridge","active":true,"usgs":false}],"preferred":false,"id":878247,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Wall, Michael","contributorId":316760,"corporation":false,"usgs":false,"family":"Wall","given":"Michael","email":"","affiliations":[{"id":16175,"text":"San Diego Natural History Museum","active":true,"usgs":false}],"preferred":false,"id":878248,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Tremor, Scott","contributorId":207768,"corporation":false,"usgs":false,"family":"Tremor","given":"Scott","email":"","affiliations":[{"id":37631,"text":"San Diego Natural History Museum, San Diego, California","active":true,"usgs":false}],"preferred":false,"id":878249,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Palenscar, Kai","contributorId":297131,"corporation":false,"usgs":false,"family":"Palenscar","given":"Kai","email":"","affiliations":[{"id":64298,"text":"San Bernardino Valley Municipal Water District","active":true,"usgs":false}],"preferred":false,"id":878250,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Fisher, Robert N. 0000-0002-2956-3240","orcid":"https://orcid.org/0000-0002-2956-3240","contributorId":51675,"corporation":false,"usgs":true,"family":"Fisher","given":"Robert N.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":878251,"contributorType":{"id":1,"text":"Authors"},"rank":18}]}}
,{"id":70268264,"text":"70268264 - 2023 - Extrusion tectonism of Indochina reassessed: constraints from 40Ar/39Ar geochronology from the Day Nui Con Voi metamorphic massif, Vietnam","interactions":[],"lastModifiedDate":"2025-06-18T14:21:46.788451","indexId":"70268264","displayToPublicDate":"2023-07-13T09:14:24","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5232,"text":"Frontiers in Earth Science","onlineIssn":"2296-6463","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Extrusion tectonism of Indochina reassessed: constraints from <sup>40</sup>Ar/<sup>39</sup/Ar geochronology from the Day Nui Con Voi metamorphic massif, Vietnam","title":"Extrusion tectonism of Indochina reassessed: constraints from 40Ar/39Ar geochronology from the Day Nui Con Voi metamorphic massif, Vietnam","docAbstract":"<p><span>The extrusion tectonic model for the southeastern margin of the Himalayan orogeny links the crustal shear activity along the Red River Shear Zone (RRSZ) to the opening of the South China Sea (SCS). The Day Nui Con Voi (DNCV) metamorphic massif in northern Vietnam strikes NW-SE, is bounded by the RRSZ to the south and continues along the strike where it meets the SCS. The DNCV is thus a critical area to document thermotectonic history in order to advance our understanding of the tectonic evolution of Indochina extrusion and its relationship to the opening of the SCS. Our new&nbsp;</span><sup>40</sup><span>Ar/</span><sup>39</sup><span>Ar data combined with microstructural and petrological analyses constrained the timing of the left-lateral shearing of the RRSZ and revealed the thermal evolution of the DNCV metamorphic massif. Three ductile deformation events were observed. D</span><sub>1</sub><span>&nbsp;formed NNW-SSE striking upright folds under granulite to upper amphibolite facies conditions. D</span><sub>2</sub><span>&nbsp;was a horizontal to sub-horizontal folding event that occurred at amphibolite facies conditions. D</span><sub>3</sub><span>&nbsp;was a doming event that formed NW-SE striking up-right folds bounded by left-lateral shearing mylonite belts along the two limbs. The S/C fabrics were defined by muscovite fish, quartz + albite + K-feldspar aggregates, and muscovite folia. The D</span><sub>3</sub><span>&nbsp;doming event exhumed the DNCV metamorphic massif from amphibolite facies conditions to the lower greenschist facies conditions. The&nbsp;</span><sup>40</sup><span>Ar/</span><sup>39</sup><span>Ar ages obtained from amphibole (∼26&nbsp;Ma), phlogopite (∼25&nbsp;Ma), muscovites (∼24-23&nbsp;Ma), biotite (∼25-23&nbsp;Ma), and K-feldspars (∼25-22&nbsp;Ma) from different structural domains of the DNCV metamorphic massif indicated a rapid exhumation ∼26–22&nbsp;Ma. We interpreted this as the time period for the D</span><sub>3</sub><span>&nbsp;event, with the onset of left-lateral shearing occurring around 24&nbsp;Ma based on ages obtained from syn-kinematic muscovites. This age was much younger than the initiation of sea-floor spreading of the SCS (since 32&nbsp;Ma) but coincided with the age for the ridge jump event in the SCS. Based on these new data, we proposed that extrusion tectonism cannot be the cause for the initial opening of the SCS. Rather, the extrusion of the Indochina block was temporally correlative with the southward ridge jump event of the already opened SCS.</span></p>","language":"English","publisher":"Frontiers Media","doi":"10.3389/feart.2023.1125279","usgsCitation":"Dinh, T., Yeh, M., Lee, T., Kunk, M., Wintsch, R., and McAleer, R.J., 2023, Extrusion tectonism of Indochina reassessed: constraints from 40Ar/39Ar geochronology from the Day Nui Con Voi metamorphic massif, Vietnam: Frontiers in Earth Science, v. 11, 1125279, 33 p., https://doi.org/10.3389/feart.2023.1125279.","productDescription":"1125279, 33 p.","ipdsId":"IP-149630","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":490983,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/feart.2023.1125279","text":"Publisher Index Page"},{"id":490907,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Vietnam","otherGeospatial":"Day Nui Con Voi massif","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              104,\n              22.5\n            ],\n            [\n              104,\n              21\n            ],\n            [\n              106,\n              21\n            ],\n            [\n              106,\n              22.5\n            ],\n            [\n              104,\n              22.5\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"11","noUsgsAuthors":false,"publicationDate":"2023-07-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Dinh, Thi-Hue","contributorId":306116,"corporation":false,"usgs":false,"family":"Dinh","given":"Thi-Hue","affiliations":[{"id":66371,"text":"Department of Earth Sciences, National Central University, Taoyuan City, Taiwan","active":true,"usgs":false}],"preferred":false,"id":940636,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yeh, Meng-Wan","contributorId":306117,"corporation":false,"usgs":false,"family":"Yeh","given":"Meng-Wan","affiliations":[{"id":66372,"text":"Department of Earth Sciences, National Taiwan Normal University, Taipei City, Taiwan","active":true,"usgs":false}],"preferred":false,"id":940637,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lee, Tung-Yi","contributorId":306118,"corporation":false,"usgs":false,"family":"Lee","given":"Tung-Yi","affiliations":[{"id":66372,"text":"Department of Earth Sciences, National Taiwan Normal University, Taipei City, Taiwan","active":true,"usgs":false}],"preferred":false,"id":940638,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kunk, Michael J. 0000-0003-4424-7825","orcid":"https://orcid.org/0000-0003-4424-7825","contributorId":291942,"corporation":false,"usgs":false,"family":"Kunk","given":"Michael J.","affiliations":[{"id":7065,"text":"USGS emeritus","active":true,"usgs":false}],"preferred":false,"id":940639,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wintsch, Robert P.","contributorId":148989,"corporation":false,"usgs":false,"family":"Wintsch","given":"Robert P.","affiliations":[{"id":12645,"text":"Indiana University - Northwest","active":true,"usgs":false}],"preferred":false,"id":940640,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McAleer, Ryan J. 0000-0003-3801-7441 rmcaleer@usgs.gov","orcid":"https://orcid.org/0000-0003-3801-7441","contributorId":215498,"corporation":false,"usgs":true,"family":"McAleer","given":"Ryan","email":"rmcaleer@usgs.gov","middleInitial":"J.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":940641,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70248941,"text":"70248941 - 2023 - Impacts of a Cascadia subduction zone earthquake on water levels and wetlands of the lower Columbia River and Estuary","interactions":[],"lastModifiedDate":"2023-09-27T12:07:10.761375","indexId":"70248941","displayToPublicDate":"2023-07-13T07:05:00","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Impacts of a Cascadia subduction zone earthquake on water levels and wetlands of the lower Columbia River and Estuary","docAbstract":"<div class=\"article-section__content en main\"><p>Subsidence after a subduction zone earthquake can cause major changes in estuarine bathymetry. Here, we quantify the impacts of earthquake-induced subsidence on hydrodynamics and habitat distributions in a major system, the lower Columbia River Estuary, using a hydrodynamic and habitat model. Model results indicate that coseismic subsidence increases tidal range, with the smallest changes at the coast and a maximum increase of ∼10% in a region of topographic convergence. All modeled scenarios reduce intertidal habitat by 24%–25% and shifts ∼93% of estuarine wetlands to lower-elevation habitat bands. Incorporating dynamic effects of tidal change from subsidence yields higher estimates of remaining habitat by multiples of 0–3.7, dependent on the habitat type. The persistent tidal change and chronic habitat disturbance after an earthquake poses strong challenges for estuarine management and wetland restoration planning, particularly when coupled with future sea-level rise effects.</p></div>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2023GL103017","usgsCitation":"Brand, M., Diefenderfer, H., O'Connor, J., Borde, A., Jay, D., Al-Bahadily, A., McKeon, M., and Talke, S., 2023, Impacts of a Cascadia subduction zone earthquake on water levels and wetlands of the lower Columbia River and Estuary: Geophysical Research Letters, v. 50, no. 14, e2023GL103017, 11 p., https://doi.org/10.1029/2023GL103017.","productDescription":"e2023GL103017, 11 p.","ipdsId":"IP-152586","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":442769,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2023gl103017","text":"Publisher Index Page"},{"id":421245,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon, Washington","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -124.73290237773512,\n              47.10099262836192\n            ],\n            [\n              -124.73290237773512,\n              44.810109654082595\n            ],\n            [\n              -121.56883987773514,\n              44.810109654082595\n            ],\n            [\n              -121.56883987773514,\n              47.10099262836192\n            ],\n            [\n              -124.73290237773512,\n              47.10099262836192\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"50","issue":"14","noUsgsAuthors":false,"publicationDate":"2023-07-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Brand, M.W.","contributorId":330189,"corporation":false,"usgs":false,"family":"Brand","given":"M.W.","email":"","affiliations":[{"id":78843,"text":"Pacific Northwest National Laboratory, Coastal Sciences Division, Sequim, WA","active":true,"usgs":false}],"preferred":false,"id":884284,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Diefenderfer, H.L.","contributorId":330190,"corporation":false,"usgs":false,"family":"Diefenderfer","given":"H.L.","affiliations":[{"id":78843,"text":"Pacific Northwest National Laboratory, Coastal Sciences Division, Sequim, WA","active":true,"usgs":false}],"preferred":false,"id":884285,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"O'Connor, Jim E. 0000-0002-7928-5883 oconnor@usgs.gov","orcid":"https://orcid.org/0000-0002-7928-5883","contributorId":140771,"corporation":false,"usgs":true,"family":"O'Connor","given":"Jim E.","email":"oconnor@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":false,"id":884286,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Borde, A.B.","contributorId":330191,"corporation":false,"usgs":false,"family":"Borde","given":"A.B.","email":"","affiliations":[{"id":78843,"text":"Pacific Northwest National Laboratory, Coastal Sciences Division, Sequim, WA","active":true,"usgs":false}],"preferred":false,"id":884287,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jay, D.A.","contributorId":174832,"corporation":false,"usgs":false,"family":"Jay","given":"D.A.","email":"","affiliations":[{"id":24698,"text":"PSU","active":true,"usgs":false}],"preferred":false,"id":884288,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Al-Bahadily, A.","contributorId":330192,"corporation":false,"usgs":false,"family":"Al-Bahadily","given":"A.","email":"","affiliations":[{"id":78845,"text":"Mustansiriyah University, Baghdad, Iraq","active":true,"usgs":false}],"preferred":false,"id":884289,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"McKeon, M.","contributorId":330193,"corporation":false,"usgs":false,"family":"McKeon","given":"M.","email":"","affiliations":[{"id":78846,"text":"Pacific Northwest National Laboratory, Coastal Sciences Division, Sequim, WA.","active":true,"usgs":false}],"preferred":false,"id":884290,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Talke, S.A.","contributorId":174831,"corporation":false,"usgs":false,"family":"Talke","given":"S.A.","email":"","affiliations":[{"id":24698,"text":"PSU","active":true,"usgs":false}],"preferred":false,"id":884291,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70247396,"text":"70247396 - 2023 - An algorithm for correction of atmospheric scattering dilution effects in volcanic gas emission measurements using skylight differential optical absorption spectroscopy","interactions":[],"lastModifiedDate":"2023-08-02T14:41:53.865058","indexId":"70247396","displayToPublicDate":"2023-07-12T09:33:15","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5232,"text":"Frontiers in Earth Science","onlineIssn":"2296-6463","active":true,"publicationSubtype":{"id":10}},"title":"An algorithm for correction of atmospheric scattering dilution effects in volcanic gas emission measurements using skylight differential optical absorption spectroscopy","docAbstract":"<p><span>Differential Optical Absorption Spectroscopy (DOAS) is commonly used to measure gas emissions from volcanoes. DOAS instruments measure the absorption of solar ultraviolet (UV) radiation scattered in the atmosphere by sulfur dioxide (SO</span><sub>2</sub><span>) and other trace gases contained in volcanic plumes. The standard spectral retrieval methods assume that all measured light comes from behind the plume and has passed through the plume along a straight line. However, a fraction of the light that reaches the instrument may have been scattered beneath the plume and thus has passed around it. Since this component does not contain the absorption signatures of gases in the plume, it effectively “dilutes” the measurements and causes underestimation of the gas abundance in the plume. This dilution effect is small for clean-air conditions and short distances between instrument and plume. However, plume measurements made at long distance and/or in conditions with significant atmospheric aerosol, haze, or clouds may be severely affected. Thus, light dilution is regarded as a major error source in DOAS measurements of volcanic degassing. Several attempts have been made to model the phenomena and the physical mechanisms are today relatively well understood. However, these models require knowledge of the local atmospheric aerosol composition and distribution, parameters that are almost always unknown. Thus, a practical algorithm to quantitatively correct for the dilution effect is still lacking. Here, we propose such an algorithm focused specifically on SO</span><sub>2</sub><span>&nbsp;measurements. The method relies on the fact that light absorption becomes non-linear for high SO</span><sub>2</sub><span>&nbsp;loads, and that strong and weak SO</span><sub>2</sub><span>&nbsp;absorption bands are unequally affected by the diluting signal. These differences can be used to identify when dilution is occurring. Moreover, if we assume that the spectral radiance of the diluting light is identical to the spectrum of light measured away from the plume, a measured clean air spectrum can be used to represent the dilution component. A correction can then be implemented by iteratively subtracting fractions of this clean air spectrum from the measured spectrum until the respective absorption signals on strong and weak SO</span><sub>2</sub><span>&nbsp;absorption bands are consistent with a single overhead SO</span><sub>2</sub><span>&nbsp;abundance. In this manner, we can quantify the magnitude of light dilution in each individual measurement spectrum as well as obtaining a dilution-corrected value for the SO</span><sub>2</sub><span>&nbsp;column density along the line of sight of the instrument. This paper first presents the theory behind the method, then discusses validation experiments using a radiative transfer model, as well as applications to field data obtained under different measurement conditions at three different locations; Fagradalsfjall located on the Reykjanaes peninsula in south Island, Manam located off the northeast coast of mainland Papua New Guinea and Holuhraun located in the inland of north east Island.</span></p>","language":"English","publisher":"Frontiers Media","doi":"10.3389/feart.2023.1088768","usgsCitation":"Galle, B., Arellano, S., Johansson, M., Kern, C., and Pfeffer, M., 2023, An algorithm for correction of atmospheric scattering dilution effects in volcanic gas emission measurements using skylight differential optical absorption spectroscopy: Frontiers in Earth Science, v. 11, 1088768, 14 p., https://doi.org/10.3389/feart.2023.1088768.","productDescription":"1088768, 14 p.","ipdsId":"IP-151840","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":442778,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/feart.2023.1088768","text":"Publisher Index Page"},{"id":419499,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11","noUsgsAuthors":false,"publicationDate":"2023-07-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Galle, Bo","contributorId":255645,"corporation":false,"usgs":false,"family":"Galle","given":"Bo","email":"","affiliations":[{"id":51629,"text":"Chalmers University, Sweden","active":true,"usgs":false}],"preferred":false,"id":879452,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Arellano, Santiago","contributorId":205719,"corporation":false,"usgs":false,"family":"Arellano","given":"Santiago","affiliations":[{"id":37153,"text":"Department of Earth and Space Sciences – Chalmers University of Technology, Göteborg, Sweden","active":true,"usgs":false}],"preferred":false,"id":879453,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Johansson, Mattias","contributorId":255657,"corporation":false,"usgs":false,"family":"Johansson","given":"Mattias","email":"","affiliations":[{"id":51629,"text":"Chalmers University, Sweden","active":true,"usgs":false}],"preferred":false,"id":879454,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kern, Christoph 0000-0002-8920-5701 ckern@usgs.gov","orcid":"https://orcid.org/0000-0002-8920-5701","contributorId":3387,"corporation":false,"usgs":true,"family":"Kern","given":"Christoph","email":"ckern@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":879455,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pfeffer, Melissa","contributorId":199349,"corporation":false,"usgs":false,"family":"Pfeffer","given":"Melissa","affiliations":[],"preferred":false,"id":879456,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70247285,"text":"70247285 - 2023 - Slip deficit rates on southern Cascadia faults resolved with viscoelastic earthquake cycle modeling of geodetic deformation","interactions":[],"lastModifiedDate":"2023-12-04T17:00:29.407097","indexId":"70247285","displayToPublicDate":"2023-07-12T08:49:38","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":"Slip deficit rates on southern Cascadia faults resolved with viscoelastic earthquake cycle modeling of geodetic deformation","docAbstract":"<p><span>The fore‐arc of the southern Cascadia subduction zone (CSZ), north of the Mendocino triple junction (MTJ), is home to a network of Quaternary‐active crustal faults that accumulate strain due to the interaction of the North American, Juan de Fuca (Gorda), and Pacific plates. These faults, including the Little Salmon and Mad River fault (LSF and MRF) zones, are located near the most populated parts of California’s north coast and show paleoseismic evidence for three slip events of several‐meter scale in the past 1700&nbsp;yr. However, the geodetic slip rates of these faults are poorly constrained. In this work, we analyze a new compilation of interseismic geodetic velocities from Global Navigation Satellite Systems, leveling, and tide gauge data near the MTJ to constrain present‐day slip deficit rates on upper‐plate faults and coupling on the megathrust. We construct Green’s functions for interseismic slip deficit for discrete faults embedded in an elastic plate overlying a viscoelastic mantle. We then use a constrained least‐squares inversion to determine best‐fitting slip rates on the major faults and investigate slip rate trade‐offs between faults. Results indicate that the LSF and MRF systems together accumulate 4–5&nbsp;mm/yr of reverse‐slip deficit, although their separate slip rates cannot be determined independently. Modeling of the horizontal and vertical velocities suggests that the southernmost CSZ is coupled interseismically to deeper than 25&nbsp;km depth. We also find that 6–17&nbsp;mm/yr of right‐lateral slip deficit extends north of the MTJ and into the southern Cascadia fore‐arc. These results reinforce the notion that both the southernmost Cascadia megathrust and the smaller fore‐arc faults above it contribute to regional seismic hazard.</span></p>","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120230007","usgsCitation":"Materna, K.Z., Murray, J.R., Pollitz, F., and Patton, J.R., 2023, Slip deficit rates on southern Cascadia faults resolved with viscoelastic earthquake cycle modeling of geodetic deformation: Bulletin of the Seismological Society of America, v. 113, no. 6, p. 2505-2518, https://doi.org/10.1785/0120230007.","productDescription":"14 p.","startPage":"2505","endPage":"2518","ipdsId":"IP-145972","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":419347,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Oregon, Washington","otherGeospatial":"Cascadia fault zone, Mendocino triple junction","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -120.02213582197189,\n              46.78612877852626\n            ],\n            [\n              -126.15645523900434,\n              46.78612877852626\n            ],\n            [\n              -126.15645523900434,\n              36.43464818238357\n            ],\n            [\n              -120.02213582197189,\n              36.43464818238357\n            ],\n            [\n              -120.02213582197189,\n              46.78612877852626\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"113","issue":"6","noUsgsAuthors":false,"publicationDate":"2023-07-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Materna, Kathryn Zerbe 0000-0002-6687-980X","orcid":"https://orcid.org/0000-0002-6687-980X","contributorId":261337,"corporation":false,"usgs":true,"family":"Materna","given":"Kathryn","email":"","middleInitial":"Zerbe","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":879116,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Murray, Jessica R. 0000-0002-6144-1681 jrmurray@usgs.gov","orcid":"https://orcid.org/0000-0002-6144-1681","contributorId":2759,"corporation":false,"usgs":true,"family":"Murray","given":"Jessica","email":"jrmurray@usgs.gov","middleInitial":"R.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":879117,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pollitz, Frederick 0000-0002-4060-2706 fpollitz@usgs.gov","orcid":"https://orcid.org/0000-0002-4060-2706","contributorId":139578,"corporation":false,"usgs":true,"family":"Pollitz","given":"Frederick","email":"fpollitz@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":879118,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Patton, Jason R.","contributorId":317714,"corporation":false,"usgs":false,"family":"Patton","given":"Jason","email":"","middleInitial":"R.","affiliations":[{"id":12640,"text":"California Geological Survey","active":true,"usgs":false}],"preferred":false,"id":879119,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70255972,"text":"70255972 - 2023 - Widespread regeneration failure in ponderosa pine forests of the southwestern United States","interactions":[],"lastModifiedDate":"2024-07-11T13:35:51.985737","indexId":"70255972","displayToPublicDate":"2023-07-12T08:28:22","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1687,"text":"Forest Ecology and Management","active":true,"publicationSubtype":{"id":10}},"title":"Widespread regeneration failure in ponderosa pine forests of the southwestern United States","docAbstract":"<p><span>As climate changes in coming decades, ponderosa pine forest persistence may be increasingly dictated by their regeneration. Sustained regeneration failure has been predicted for forests of the southwestern US (SWUS) even in absence of stand-replacing wildfire, but regeneration in undisturbed and lightly disturbed forests has been studied infrequently and at a limited number of locations. We characterized 77 ponderosa pine sites in 7 SWUS locations, documented regeneration occurring over the past&nbsp;</span><span class=\"math\"><span id=\"MathJax-Element-1-Frame\" class=\"MathJax_SVG\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><mrow is=&quot;true&quot;><mo is=&quot;true&quot;>&amp;#x223C;</mo></mrow></math>\"><span class=\"MJX_Assistive_MathML\">∼</span></span></span><span>20&nbsp;years, and utilized gridded meteorological estimates and water balance modeling to determine the climate and environmental conditions associated with regeneration failure (R0). Of these sites, 29</span><span class=\"math\"><span id=\"MathJax-Element-2-Frame\" class=\"MathJax_SVG\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><mrow is=&quot;true&quot;><mo is=&quot;true&quot;>%</mo></mrow></math>\"><span class=\"MJX_Assistive_MathML\">%</span></span></span><span>&nbsp;were R0, illuminating that regeneration failure in these forests is widespread. R0 sites were distinguished by high above- and belowground heat loading, loss of cool-season climate, and high soil moisture variation. Explanatory variables had high accuracy in identifying R0 sites, and illustrate the climate-driven pathway by which regeneration failure has occurred in the SWUS. Regeneration failure has high potential to increase in a warmer, more hydrologically variable climate, and expand regionally from lower to higher latitudes. Yet, we also found that human management interventions were associated with environmental conditions that avoided regeneration failure. To counteract regeneration-associated forest declines, interventions will need to influence climate-driven environmental change by adjusting forest characteristics at local scales. Regeneration failures are a major threat to ponderosa pine forest persistence, and they have potential to intensify and expand in a changing climate.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.foreco.2023.121208","usgsCitation":"Petrie, M., Hubbard, R.M., Bradford, J., Kolb, T.E., Noel, A.R., Schlaepfer, D.R., Bowen, M., Fuller, L., and Moser, W., 2023, Widespread regeneration failure in ponderosa pine forests of the southwestern United States: Forest Ecology and Management, v. 545, 121208, 13 p., https://doi.org/10.1016/j.foreco.2023.121208.","productDescription":"121208, 13 p.","ipdsId":"IP-152261","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":442782,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.foreco.2023.121208","text":"Publisher Index Page"},{"id":430955,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, Colorado, Nevada, New Mexico","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -105.88234100540745,\n              37.05581076916032\n            ],\n            [\n              -104.24583815503905,\n              38.9431487321456\n            ],\n            [\n              -106.24666332057024,\n              39.8044030231502\n            ],\n            [\n              -108.95797164480376,\n              36.82454106093326\n            ],\n            [\n              -115.40763496916662,\n              36.58313667272253\n            ],\n            [\n              -115.86898184601188,\n              36.398755822605594\n            ],\n    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0000-0003-2601-1798","orcid":"https://orcid.org/0000-0003-2601-1798","contributorId":334944,"corporation":false,"usgs":false,"family":"Hubbard","given":"Robert","email":"","middleInitial":"M.","affiliations":[{"id":80290,"text":"USDA Forest Service, Rocky Mountain Research Station, Fort Collins, CO 80521, USA","active":true,"usgs":false}],"preferred":false,"id":906179,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bradford, John B. 0000-0001-9257-6303","orcid":"https://orcid.org/0000-0001-9257-6303","contributorId":219257,"corporation":false,"usgs":true,"family":"Bradford","given":"John B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":906180,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kolb, Tom E.","contributorId":340095,"corporation":false,"usgs":false,"family":"Kolb","given":"Tom","email":"","middleInitial":"E.","affiliations":[{"id":39356,"text":"School of Forestry, Northern Arizona University, Flagstaff, AZ, 86011, USA","active":true,"usgs":false}],"preferred":false,"id":906181,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Noel, Adam Roy 0000-0002-0891-4005","orcid":"https://orcid.org/0000-0002-0891-4005","contributorId":294761,"corporation":false,"usgs":true,"family":"Noel","given":"Adam","email":"","middleInitial":"Roy","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":906182,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Schlaepfer, Daniel Rodolphe 0000-0001-9973-2065","orcid":"https://orcid.org/0000-0001-9973-2065","contributorId":225569,"corporation":false,"usgs":true,"family":"Schlaepfer","given":"Daniel","email":"","middleInitial":"Rodolphe","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":906183,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bowen, M.A.","contributorId":340096,"corporation":false,"usgs":false,"family":"Bowen","given":"M.A.","email":"","affiliations":[{"id":81462,"text":"USDA Forest Service, Lincoln National Forest, Cloudcroft, NM, USA","active":true,"usgs":false}],"preferred":false,"id":906184,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Fuller, L.R.","contributorId":340098,"corporation":false,"usgs":false,"family":"Fuller","given":"L.R.","email":"","affiliations":[{"id":81463,"text":"USDA Forest Service, Apache-Sitgreaves National Forest, Springerville, AZ, USA","active":true,"usgs":false}],"preferred":false,"id":906185,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Moser, W. Keith","contributorId":298271,"corporation":false,"usgs":false,"family":"Moser","given":"W. Keith","affiliations":[{"id":7062,"text":"University of Oklahoma","active":true,"usgs":false}],"preferred":false,"id":906186,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70246685,"text":"70246685 - 2023 - Minimal shift of eastern wild turkey nesting phenology associated with projected climate change","interactions":[],"lastModifiedDate":"2023-07-26T14:50:52.169626","indexId":"70246685","displayToPublicDate":"2023-07-12T06:57:02","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":12584,"text":"Climate Change Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Minimal shift of eastern wild turkey nesting phenology associated with projected climate change","docAbstract":"<div id=\"abstracts\" class=\"Abstracts u-font-gulliver text-s\"><div id=\"abs0002\" class=\"abstract author\"><div id=\"abss0002\"><p id=\"spara010\">Climate change may induce mismatches between wildlife reproductive phenology and temporal occurrence of resources necessary for reproductive success. Verifying and elucidating the causal mechanisms behind potential mismatches requires large-scale, longer-duration data. We used eastern wild turkey (<i>Meleagris gallopavo silvestris</i>) nesting data collected across the southeastern U.S. over eight years to investigate potential climatic drivers of variation in nest initiation dates. We investigated climactic relationships with two datasets, one inclusive of successful and unsuccessful nests (full dataset) and another of just successful nests (successfully hatched dataset), to determine whether successfully hatched nests responded differently to weather changes than all nests did. In the full dataset, each 10 cm increase in January precipitation was associated with nesting occurring 0.46-0.66 days earlier, and each 10 cm increase in precipitation during the 30 days preceding nesting was associated with nesting occurring 0.17-0.21 days later. In the successfully hatched dataset, a 10 cm increase in March precipitation was associated with nesting occurring 0.67-0.74 days earlier, and an increase of one unit of variation in February maximum temperature was associated with nesting occurring 0.02 days later. We combined the results of these modeled relationships with multiple climate scenarios to understand potential implications of future climate change on wild turkey nesting phenology; results indicated that mean nest initiation date is projected to change by &lt;0.1 day by 2040-2060. Wild turkey nesting phenology did not track changes in spring green-up timing, which could result in phenological mismatch between the timing of nesting and the availability of resources critical for successful reproduction.</p></div></div></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecochg.2023.100075","usgsCitation":"Boone, W.W., Moorman, C.E., Terando, A., Moscicki, D.J., Collier, B.A., Chamberlain, M.J., and Pacifici, K., 2023, Minimal shift of eastern wild turkey nesting phenology associated with projected climate change: Climate Change Ecology, v. 6, 100075, 11 p., https://doi.org/10.1016/j.ecochg.2023.100075.","productDescription":"100075, 11 p.","ipdsId":"IP-152227","costCenters":[{"id":40926,"text":"Southeast Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":442786,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecochg.2023.100075","text":"Publisher Index Page"},{"id":418942,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -94.75209580002951,\n              32.25320074896807\n            ],\n            [\n              -95.0815205573511,\n              29.521888357653637\n            ],\n            [\n              -90.2088882473733,\n              30.174374401452027\n            ],\n            [\n              -83.64390510481638,\n              30.333829865871834\n            ],\n            [\n              -81.07746537957816,\n              31.906625399783778\n            ],\n            [\n              -77.70532006878682,\n              34.77774124205962\n            ],\n            [\n              -77.15343272040974,\n              35.772505240501715\n            ],\n            [\n              -82.15918234004386,\n              36.11922121375349\n            ],\n            [\n              -84.97052151037536,\n              33.72912641315099\n            ],\n            [\n              -85.49679462199073,\n              31.83341615083944\n            ],\n            [\n              -94.75209580002951,\n              32.25320074896807\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"6","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Boone, Wesley W.","contributorId":316654,"corporation":false,"usgs":false,"family":"Boone","given":"Wesley","email":"","middleInitial":"W.","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":877941,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Moorman, Christopher E.","contributorId":140839,"corporation":false,"usgs":false,"family":"Moorman","given":"Christopher","email":"","middleInitial":"E.","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":877942,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Terando, Adam 0000-0002-9280-043X","orcid":"https://orcid.org/0000-0002-9280-043X","contributorId":205908,"corporation":false,"usgs":true,"family":"Terando","given":"Adam","affiliations":[{"id":565,"text":"Southeast Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":877943,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Moscicki, David J.","contributorId":316655,"corporation":false,"usgs":false,"family":"Moscicki","given":"David","email":"","middleInitial":"J.","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":877944,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Collier, Bret A.","contributorId":316656,"corporation":false,"usgs":false,"family":"Collier","given":"Bret","email":"","middleInitial":"A.","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":877945,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Chamberlain, Michael J.","contributorId":179350,"corporation":false,"usgs":false,"family":"Chamberlain","given":"Michael","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":877946,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Pacifici, Krishna","contributorId":244494,"corporation":false,"usgs":false,"family":"Pacifici","given":"Krishna","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":877947,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70246687,"text":"70246687 - 2023 - Combining expert knowledge of a threatened trout distribution with sparse occupancy data for climate-related projection","interactions":[],"lastModifiedDate":"2023-07-14T11:48:37.539996","indexId":"70246687","displayToPublicDate":"2023-07-12T06:41:43","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":"Combining expert knowledge of a threatened trout distribution with sparse occupancy data for climate-related projection","docAbstract":"<h3 id=\"nafm10905-sec-1001-title\" class=\"article-section__sub-title section\">Objective</h3><p>To evaluate the vulnerability of Bull Trout<span>&nbsp;</span><i>Salvelinus confluentus</i><span>&nbsp;</span>to potential climate changes across its range in Oregon, we compiled disparate expert knowledge of the distribution of spawning and rearing and combined these probabilistic statements as data along with documented records of breeding and rearing in a joint occupancy model.</p><h3 id=\"nafm10905-sec-1002-title\" class=\"article-section__sub-title section\">Methods</h3><p>The joint expert knowledge–occupancy model, which was based on discrete patches of cold water (≤13°C) suitable for spawning and rearing, permitted the association of true occupancy with climate and other explanatory variables while accounting for variation in detection probability. We then applied estimated relationships of patch occupancy with explanatory variables to projected coldwater patch configurations in the years 2040 and 2080.</p><h3 id=\"nafm10905-sec-1003-title\" class=\"article-section__sub-title section\">Result</h3><p>Projections of the kilometers of occupied coldwater patch in future decades suggest precipitous declines if current relationships of occupancy with environmental variables are maintained. Impacts of climate changes in future decades manifest directly through the outright loss of coldwater patches and increases in winter high flows but also indirectly by increased isolation.</p><h3 id=\"nafm10905-sec-1004-title\" class=\"article-section__sub-title section\">Conclusion</h3><p>Combining probabilistic statements of species distributions from knowledgeable experts with sparse occupancy data may be a robust and timely alternative when large numbers of repeated occupancy surveys are infeasible.</p>","language":"English","publisher":"American Fisheries Society","doi":"10.1002/nafm.10905","usgsCitation":"Chelgren, N., Dunham, J., Gunckel, S.L., Hockman-Wert, D.P., and Allen, C.S., 2023, Combining expert knowledge of a threatened trout distribution with sparse occupancy data for climate-related projection: North American Journal of Fisheries Management, v. 43, no. 3, p. 839-858, https://doi.org/10.1002/nafm.10905.","productDescription":"20 p.","startPage":"839","endPage":"858","ipdsId":"IP-139349","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":498031,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/nafm.10905","text":"Publisher Index Page"},{"id":418940,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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,{"id":70246571,"text":"tm15E1 - 2023 - White-Nose Syndrome Diagnostic Laboratory Network handbook","interactions":[{"subject":{"id":70246571,"text":"tm15E1 - 2023 - White-Nose Syndrome Diagnostic Laboratory Network handbook","indexId":"tm15E1","publicationYear":"2023","noYear":false,"displayTitle":"White-Nose Syndrome Diagnostic Laboratory Network Handbook","title":"White-Nose Syndrome Diagnostic Laboratory Network handbook"},"predicate":"IS_PART_OF","object":{"id":70118922,"text":"tm15 - 2015 - Field Manual of Wildlife Diseases","indexId":"tm15","publicationYear":"2015","noYear":false,"title":"Field Manual of Wildlife Diseases"},"id":1}],"isPartOf":{"id":70118922,"text":"tm15 - 2015 - Field Manual of Wildlife Diseases","indexId":"tm15","publicationYear":"2015","noYear":false,"title":"Field Manual of Wildlife Diseases"},"lastModifiedDate":"2023-07-11T16:22:57.262049","indexId":"tm15E1","displayToPublicDate":"2023-07-11T11:09:53","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":"15-E1","displayTitle":"White-Nose Syndrome Diagnostic Laboratory Network Handbook","title":"White-Nose Syndrome Diagnostic Laboratory Network handbook","docAbstract":"<p>When responding to a wildlife disease outbreak, managers depend on consistent and clear data to make decisions. However, diagnostic methods for detecting pathogens of wildlife often lack the level of procedural and interpretational standardization that occurs in the investigation of human and domestic animal diseases. This lack of standardization can hamper diagnostic reliability in two ways. First is the inappropriate application of tests to new species or in situations that are outside of the original (in other words, validated) purpose. Second is the use of laboratory-specific modifications or analytical parameters without thorough investigation of how those changes affect result comparisons across institutions or the ability to make broader conclusions about pathogen or disease.</p><p>White-nose syndrome (WNS) is a disease caused by the fungal pathogen <i>Pseudogymnoascus destructans</i> (<i>Pd</i>), which has spread rapidly and is causing population-level declines in some species of North American bats. During the last decade, quantitative polymerase chain reaction (qPCR) has become the most common method of testing for <i>Pd</i> because of qPCR’s speed, accuracy, and simplicity across a wide range of invasive and noninvasive sample types. Its widespread use by many State, Federal, Provincial, and academic institutions has inevitably led to variations in methodology and interpretation among laboratories. The progressive geographic spread of fungus and disease has also led to sampling contexts and strategies that differ from those for which the qPCR assay was originally developed and validated. These factors have resulted in inconsistencies among results tested in different laboratories and, subsequently, confusion for managers and decision makers.</p><p>To address these challenges, the WNS National Response Team Diagnostic Working Group launched a project congruent with increased calls for the harmonization of wildlife disease diagnostic results, and reporting standards across disparate methodologies and laboratories. Beginning in 2019, interlaboratory testing was done to better understand how variations to <i>Pd</i> qPCR methodology affect diagnostic consistency and to reassess the assay’s fit for purpose in new testing contexts. This information led to expanded conversations within the Diagnostic Working Group related to best practices in <i>Pd</i> qPCR diagnostic testing, the development of common interpretation language for classifying test results, and the incorporation of that language into an updated WNS case definition. This handbook is the resulting product and is intended to help further harmonize <i>Pd</i> qPCR diagnostic testing by establishing recommendations related to voluntary participation in a WNS Diagnostic Laboratory Network, documenting the currently (2022) practiced <i>Pd</i> qPCR methodologies, discussing general best practices for molecular diagnostics and laboratory networks, and elaborating on the epidemiologic and diagnostic basis of the agreed-upon classification language for <i>Pd</i> qPCR results. Through this voluntary, consensus-based approach to diagnostic harmonization, this work aims to improve the confidence of management agencies in reported <i>Pd</i> qPCR results and can serve as an example of national diagnostic coordination for other unregulated wildlife diseases.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm15E1","usgsCitation":"Alger, K., and White Nose Syndrome National Response Team Diagnostic Working Group, 2023, White-Nose Syndrome Diagnostic Laboratory Network handbook: U.S. Geological Survey Techniques and Methods, book 15, chap. E1, 50 p., https://doi.org/10.3133/tm15E1.","productDescription":"Report: x, 50 p.; Data Release","numberOfPages":"64","onlineOnly":"Y","ipdsId":"IP-137564","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":418802,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/tm/15/e01/coverthb.jpg"},{"id":418803,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/15/e01/tm15e1.pdf","text":"Report","size":"4.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"T&M 15–E1"},{"id":418805,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/tm/15/e01/tm15e1.XML"},{"id":418806,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/tm/15/e01/images/"},{"id":418808,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P93SXYL0","text":"USGS Data Release","linkHelpText":"<em>Pd</em> qPCR interlaboratory testing results"}],"contact":"<p>Director, <a href=\"https://www.usgs.gov/centers/nwhc\" data-mce-href=\"https://www.usgs.gov/centers/nwhc\">National Wildlife Health Center</a><br>U.S. Geological Survey<br>6006 Schroeder Road<br>Madison, WI 53711</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>White-Nose Syndrome Response Team Diagnostic and Surveillance Working Group</li><li>Standardization Versus Harmonization</li><li>Purpose and Scope</li><li>Principles of Wildlife Disease Sampling with Additional Resources</li><li>Sampling Considerations for <i>Pseudogymnoascus destructans</i></li><li>Laboratory Biosecurity and Quality Management Systems</li><li><i>Pseudogymnoascus destructans</i> Molecular Detection Methods (Deoxyribonucleic Acid Extraction and Quantitative Polymerase Chain Reaction)</li><li>Best Management Practices for Laboratory Network Participation</li><li>Summary</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2023-07-11","noUsgsAuthors":false,"publicationDate":"2023-07-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Alger, Katrina E. 0000-0001-7708-0203","orcid":"https://orcid.org/0000-0001-7708-0203","contributorId":228815,"corporation":false,"usgs":true,"family":"Alger","given":"Katrina","email":"","middleInitial":"E.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":877250,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"White Nose Syndrome National Response Team Diagnostic Working Group","contributorId":316267,"corporation":true,"usgs":false,"organization":"White Nose Syndrome National Response Team Diagnostic Working Group","id":877251,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70247088,"text":"70247088 - 2023 - Differentiable modelling to unify machine learning and physical models for geosciences","interactions":[],"lastModifiedDate":"2023-08-08T14:28:33.208368","indexId":"70247088","displayToPublicDate":"2023-07-11T08:23:49","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7460,"text":"Nature Reviews Earth & Environment","active":true,"publicationSubtype":{"id":10}},"title":"Differentiable modelling to unify machine learning and physical models for geosciences","docAbstract":"<p><span>Process-based modelling offers interpretability and physical consistency in many domains of geosciences but struggles to leverage large datasets efficiently. Machine-learning methods, especially deep networks, have strong predictive skills yet are unable to answer specific scientific questions. In this Perspective, we explore differentiable modelling as a pathway to dissolve the perceived barrier between process-based modelling and machine learning in the geosciences and demonstrate its potential with examples from hydrological modelling. ‘Differentiable’ refers to accurately and efficiently calculating gradients with respect to model variables or parameters, enabling the discovery of high-dimensional unknown relationships. Differentiable modelling involves connecting (flexible amounts of) prior physical knowledge to neural networks, pushing the boundary of physics-informed machine learning. It offers better interpretability, generalizability, and extrapolation capabilities than purely data-driven machine learning, achieving a similar level of accuracy while requiring less training data. Additionally, the performance and efficiency of differentiable models scale well with increasing data volumes. Under data-scarce scenarios, differentiable models have outperformed machine-learning models in producing short-term dynamics and decadal-scale trends owing to the imposed physical constraints. Differentiable modelling approaches are primed to enable geoscientists to ask questions, test hypotheses, and discover unrecognized physical relationships. Future work should address computational challenges, reduce uncertainty, and verify the physical significance of outputs.</span></p>","language":"English","publisher":"Springer Nature","doi":"10.1038/s43017-023-00450-9","usgsCitation":"Shen, C., Appling, A.P., Gentine, P., Bandai, T., Gupta, H., Tartakovsky, A., Baity-Jesi, M., Fenicia, F., Kifer, D., Li, L., Liu, X., Ren, W., Zheng, Y., Harman, C., Clark, M., Farthing, M., Feng, D., Kumar, P., Aboelyazeed, D., Rahmani, F., Song, Y., Beck, H.E., Bindas, T., Dwivedi, D., Fang, K., Hoge, M., Rackauckas, C., Mohanty, B., , R., Xu, C., and Lawson, K., 2023, Differentiable modelling to unify machine learning and physical models for geosciences: Nature Reviews Earth & Environment, v. 4, p. 552-567, https://doi.org/10.1038/s43017-023-00450-9.","productDescription":"16 p.","startPage":"552","endPage":"567","ipdsId":"IP-147269","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":467103,"rank":2,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/10150/672240","text":"External Repository"},{"id":419241,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"4","noUsgsAuthors":false,"publicationDate":"2023-07-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Shen, Chaopeng","contributorId":152465,"corporation":false,"usgs":false,"family":"Shen","given":"Chaopeng","email":"","affiliations":[{"id":7260,"text":"Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":878568,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Appling, Alison P. 0000-0003-3638-8572 aappling@usgs.gov","orcid":"https://orcid.org/0000-0003-3638-8572","contributorId":150595,"corporation":false,"usgs":true,"family":"Appling","given":"Alison","email":"aappling@usgs.gov","middleInitial":"P.","affiliations":[{"id":5054,"text":"Office of Water Information","active":true,"usgs":true}],"preferred":true,"id":878569,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gentine, Pierre 0000-0002-0845-8345","orcid":"https://orcid.org/0000-0002-0845-8345","contributorId":317070,"corporation":false,"usgs":false,"family":"Gentine","given":"Pierre","email":"","affiliations":[{"id":68928,"text":"National Science Foundation Science and Technology Center for Learning the Earth with Artificial Intelligence and Physics (LEAP), Columbia University, New York, NY USA","active":true,"usgs":false}],"preferred":false,"id":878570,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bandai, Toshiyuki 0000-0003-4165-5436","orcid":"https://orcid.org/0000-0003-4165-5436","contributorId":317071,"corporation":false,"usgs":false,"family":"Bandai","given":"Toshiyuki","email":"","affiliations":[{"id":68929,"text":"Life and Environmental Science Department, University of California, Merced, CA, USA","active":true,"usgs":false}],"preferred":false,"id":878571,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gupta, Hoshin","contributorId":261624,"corporation":false,"usgs":false,"family":"Gupta","given":"Hoshin","affiliations":[{"id":52935,"text":"Department of Hydrology and Atmospheric Sciences, University of Arizona, Tucson, AZ","active":true,"usgs":false}],"preferred":false,"id":878572,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Tartakovsky, Alexandre 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University Park, PA, USA","active":true,"usgs":false}],"preferred":false,"id":878583,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Kumar, Praveen 0000-0002-4787-0308","orcid":"https://orcid.org/0000-0002-4787-0308","contributorId":256753,"corporation":false,"usgs":false,"family":"Kumar","given":"Praveen","email":"","affiliations":[{"id":36403,"text":"University of Illinois","active":true,"usgs":false}],"preferred":false,"id":878584,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Aboelyazeed, Doaa","contributorId":317079,"corporation":false,"usgs":false,"family":"Aboelyazeed","given":"Doaa","email":"","affiliations":[{"id":68932,"text":"Civil and Environmental Engineering, The Pennsylvania State University, University Park, PA, USA","active":true,"usgs":false}],"preferred":false,"id":878585,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Rahmani, 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0000-0001-5850-0663","orcid":"https://orcid.org/0000-0001-5850-0663","contributorId":317085,"corporation":false,"usgs":false,"family":"Rackauckas","given":"Chris","email":"","affiliations":[{"id":68937,"text":"Computer Science and Artificial Intelligence Laboratory (CSAIL), Massachusetts Institute of Technology, Massachusetts, USA","active":true,"usgs":false}],"preferred":false,"id":878592,"contributorType":{"id":1,"text":"Authors"},"rank":27},{"text":"Mohanty, Binayak 0000-0001-9381-7279","orcid":"https://orcid.org/0000-0001-9381-7279","contributorId":244961,"corporation":false,"usgs":false,"family":"Mohanty","given":"Binayak","email":"","affiliations":[{"id":6747,"text":"Texas A&M University","active":true,"usgs":false}],"preferred":false,"id":878875,"contributorType":{"id":1,"text":"Authors"},"rank":28},{"text":" Roy 0000-0002-6279-8447","orcid":"https://orcid.org/0000-0002-6279-8447","contributorId":317086,"corporation":false,"usgs":false,"given":"Roy","email":"","affiliations":[{"id":68938,"text":"Civil and Environmental Engineering, University of Nebraska-Lincoln, NE, USA","active":true,"usgs":false}],"preferred":false,"id":878593,"contributorType":{"id":1,"text":"Authors"},"rank":29},{"text":"Xu, Chonggang","contributorId":207944,"corporation":false,"usgs":false,"family":"Xu","given":"Chonggang","email":"","affiliations":[],"preferred":false,"id":878594,"contributorType":{"id":1,"text":"Authors"},"rank":30},{"text":"Lawson, Kathryn","contributorId":265776,"corporation":false,"usgs":false,"family":"Lawson","given":"Kathryn","affiliations":[{"id":54792,"text":"Civil and Environmental Engineering, Pennsylvania State University, University Park, PA","active":true,"usgs":false}],"preferred":false,"id":878595,"contributorType":{"id":1,"text":"Authors"},"rank":31}]}}
,{"id":70246733,"text":"70246733 - 2023 - Ring fault creep drives volcano-tectonic seismicity during caldera collapse of Kīlauea in 2018","interactions":[],"lastModifiedDate":"2023-07-18T11:57:32.785185","indexId":"70246733","displayToPublicDate":"2023-07-11T06:53:35","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1427,"text":"Earth and Planetary Science Letters","active":true,"publicationSubtype":{"id":10}},"title":"Ring fault creep drives volcano-tectonic seismicity during caldera collapse of Kīlauea in 2018","docAbstract":"<div id=\"preview-section-abstract\"><div id=\"abstracts\" class=\"Abstracts u-font-gulliver text-s\"><div id=\"ab0010\" class=\"abstract author\"><div id=\"as0010\"><p id=\"sp0090\">Basaltic caldera collapses are episodic, producing very-long-period (VLP) earthquakes up to M<sub>w</sub><span>&nbsp;5.4, with prolific inter-collapse (between collapses) volcano-tectonic (VT)&nbsp;seismicity. During the 2018 caldera collapse of Kīlauea Volcano, VT&nbsp;seismicity&nbsp;ceased following each collapse, and then accelerated to a quasi-steady rate prior to the next collapse, marking a temporal pattern distinct from typical foreshock/aftershock sequences. There is currently no consensus on the mechanism(s) that generates the VT seismicity. Here we demonstrate that inter-collapse ring fault creep, induced by chamber depressurization, was the main driver of VT seismicity at Kīlauea in 2018. This is evidenced by: 1) the correlation between cumulative number of VT events and GNSS-derived ring fault creep; 2) agreement between repeating earthquake and&nbsp;GNSS&nbsp;derived creep rates; and 3) consistency between the time dependence of mechanically modeled, creep-driven seismicity and observations. We further show that, ring fault creep can be explained by velocity strengthening friction alone or in conjunction with viscous shear zone rheology. The simultaneous occurrence of creep and seismicity highlights the spatially heterogeneous velocity weakening/strengthening friction on the ring fault. If the VT seismicity-creep correlation can be replicated at other basaltic volcanoes, it would demonstrate that VT seismicity can be used as a proxy for ring fault creep in the absence of&nbsp;GNSS&nbsp;measurements on subsiding caldera block(s).</span></p></div></div></div></div><div id=\"preview-section-introduction\"><br></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.epsl.2023.118288","usgsCitation":"Wang, T.A., Segall, P., Hotovec-Ellis, A.J., Anderson, K.R., and Cervelli, P.F., 2023, Ring fault creep drives volcano-tectonic seismicity during caldera collapse of Kīlauea in 2018: Earth and Planetary Science Letters, v. 618, 118288, https://doi.org/10.1016/j.epsl.2023.118288.","productDescription":"118288","ipdsId":"IP-150462","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":442806,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.epsl.2023.118288","text":"Publisher Index Page"},{"id":419041,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Kīlauea","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -155.49702282191438,\n              19.617923166680413\n            ],\n            [\n              -155.49702282191438,\n              19.084322876546395\n            ],\n            [\n              -154.9149971510316,\n              19.084322876546395\n            ],\n            [\n              -154.9149971510316,\n              19.617923166680413\n            ],\n            [\n              -155.49702282191438,\n              19.617923166680413\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"618","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Wang, Taiyi A. 0000-0002-5933-6866","orcid":"https://orcid.org/0000-0002-5933-6866","contributorId":316717,"corporation":false,"usgs":false,"family":"Wang","given":"Taiyi","email":"","middleInitial":"A.","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":878123,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Segall, Paul","contributorId":241093,"corporation":false,"usgs":false,"family":"Segall","given":"Paul","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":878124,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hotovec-Ellis, Alicia J. 0000-0003-1917-0205","orcid":"https://orcid.org/0000-0003-1917-0205","contributorId":211785,"corporation":false,"usgs":true,"family":"Hotovec-Ellis","given":"Alicia","email":"","middleInitial":"J.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":878125,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Anderson, Kyle R. 0000-0001-8041-3996 kranderson@usgs.gov","orcid":"https://orcid.org/0000-0001-8041-3996","contributorId":3522,"corporation":false,"usgs":true,"family":"Anderson","given":"Kyle","email":"kranderson@usgs.gov","middleInitial":"R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":878126,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cervelli, Peter F.","contributorId":214424,"corporation":false,"usgs":false,"family":"Cervelli","given":"Peter","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":878127,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70245537,"text":"sir20235071 - 2023 - Assessment of salinity retention or mobilization by sediment-retention ponds near Delta, Colorado, 2019","interactions":[],"lastModifiedDate":"2026-03-09T17:12:27.818572","indexId":"sir20235071","displayToPublicDate":"2023-07-10T17:45:00","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":"2023-5071","displayTitle":"Assessment of Salinity Retention or Mobilization by Sediment-Retention Ponds near Delta, Colorado, 2019","title":"Assessment of salinity retention or mobilization by sediment-retention ponds near Delta, Colorado, 2019","docAbstract":"<p>Salinity control efforts in the Colorado River Basin have focused on mobilization of salts from irrigated land, but nonirrigated rangelands are also a source of salinity. In particular, lands where soils have formed from the Late Cretaceous Mancos Shale under arid and semiarid climates contain considerable quantities of salt, mainly in the subsurface. Hundreds of thousands of contour furrows and check dams (gully plugs) were constructed by the Bureau of Land Management (BLM) and Bureau of Reclamation in the late 1950s and 1960s to reduce runoff, sedimentation, and salt mobilization from ephemeral stream channels on rangelands. Sediment-retention ponds associated with check dams are dry most of the year, except immediately following substantial rain events. Generally, no maintenance has been performed on these structures, some have degraded over time, and their current and past influence on salinity is poorly understood. To assess the influence of check dams and their associated ponds on salt retention and mobilization, the U.S. Geological Survey, in cooperation with the BLM, conducted a study of such ponds within the Gunnison Gorge National Conservation Area (GGNCA) near Delta, Colorado.</p><p>This report includes conceptual models of how sediment-retention ponds function relative to salinity, and a collection of environmental data to evaluate the conceptual models. An inventory of 69 ponds indicated that 38 percent no longer had water holding capacity, and another 20 percent could hold 1 foot or less of water. Check-dam degradation was the main cause, but sediment infill of ponds contributed as well. Water content of soil profiles collected beneath ponds and immediately downstream from check dams indicated little penetration of water below 60 centimeters for most ponds and little evidence for lateral movement of water beneath check dams. Patterns of salt content in the soil profiles indicated no accumulation of salts at the pond surface from evaporating waters and little evidence for salt redistribution in the form of salt bulges or salt depletion curves at intermediate depths. Based on the conceptual models presented and interpretations of data collected by this study, it appears that the sediment-retention ponds in the GGNCA have neither mobilized nor retained substantial quantities of salt during their lifetimes.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235071","collaboration":"Prepared in cooperation with Bureau of Land Management","programNote":"Water Availability and Use Science Program","usgsCitation":"Richards, R.J., Bern, C.R., and Moreno, V., 2023, Assessment of salinity retention or mobilization by sediment-retention ponds near Delta, Colorado, 2019: U.S. Geological Survey Scientific Investigations Report 2023–5071, 21 p., https://doi.org/10.3133/sir20235071.","productDescription":"Report: v, 21 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-134766","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":418430,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9WZNJL6","text":"USGS data release","linkHelpText":"Data from the assessment of sediment-retention ponds near Delta, Colorado, 2019"},{"id":418428,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5071/coverthb.jpg"},{"id":418429,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5071/sir20235071.pdf","text":"Report","size":"4.39 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023-5071"},{"id":500951,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114965.htm","linkFileType":{"id":5,"text":"html"}},{"id":418866,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.er.usgs.gov/publication/sir20235071/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2023-5071"},{"id":418837,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5071/sir20235071.xml"},{"id":418836,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5071/images"}],"country":"United States","state":"Colorado","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -107.55,\n              38.4\n            ],\n            [\n              -107.55,\n              38.36\n            ],\n            [\n              -107.53,\n              38.36\n            ],\n            [\n              -107.53,\n              38.4\n            ],\n            [\n              -107.55,\n              38.4\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","contact":"<p>Director, <a href=\"https://www.usgs.gov/centers/colorado-water-science-center/\" data-mce-href=\"https://www.usgs.gov/centers/colorado-water-science-center/\">Colorado Water Science Center</a><br>U.S. Geological Survey<br>Box 25048, Mail Stop 415<br>Denver, Colorado 80225</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Conceptual Models of Pond and Salinity Interactions</li><li>Methods of Data Collection and Analysis</li><li>Sediment-Retention Pond Inventory and Soil-Profile Properties</li><li>Assessment of Salinity Retention or Mobilization by Sediment-Retention Ponds</li><li>Summary</li><li>References Cited</li></ul>","publishedDate":"2023-07-10","noUsgsAuthors":false,"publicationDate":"2023-07-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Richards, Rodney J. 0000-0003-3953-984X","orcid":"https://orcid.org/0000-0003-3953-984X","contributorId":202708,"corporation":false,"usgs":true,"family":"Richards","given":"Rodney J.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":876144,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bern, Carleton R. 0000-0002-8980-1781 cbern@usgs.gov","orcid":"https://orcid.org/0000-0002-8980-1781","contributorId":201152,"corporation":false,"usgs":true,"family":"Bern","given":"Carleton","email":"cbern@usgs.gov","middleInitial":"R.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":876145,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Moreno, Victoria 0000-0001-8138-9086","orcid":"https://orcid.org/0000-0001-8138-9086","contributorId":312085,"corporation":false,"usgs":false,"family":"Moreno","given":"Victoria","email":"","affiliations":[{"id":67581,"text":"USGS volunteer - University of Texas at El Paso","active":true,"usgs":false}],"preferred":false,"id":876146,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70256453,"text":"70256453 - 2023 - Efficacy of machine learning image classification for automated occupancy-based monitoring","interactions":[],"lastModifiedDate":"2024-08-02T13:40:19.411631","indexId":"70256453","displayToPublicDate":"2023-07-10T14:47:48","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5347,"text":"Remote Sensing in Ecology and Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Efficacy of machine learning image classification for automated occupancy-based monitoring","docAbstract":"<p><span>Remote cameras have become a widespread data-collection tool for terrestrial mammals, but classifying images can be labor intensive and limit the usefulness of cameras for broad-scale population monitoring. Machine learning algorithms for automated image classification can expedite data processing, but image misclassifications may influence inferences. Here, we used camera data for three sympatric species with disparate body sizes and life histories – black-tailed jackrabbits (</span><i>Lepus californicus</i><span>), kit foxes (</span><i>Vulpes macrotis</i><span>), and pronghorns (</span><i>Antilocapra americana</i><span>) – as a model system to evaluate the influence of competing image classification approaches on estimates of occupancy and inferences about space use. We classified images with: (i) single review (manual), (ii) double review (manual by two observers), (iii) an automated-manual review (machine learning to cull empty images and single review of remaining images), (iv) a pretrained machine-learning algorithm that classifies images to species (base model), (v) the base model accepting only classifications with ≥95% confidence, (vi) the base model trained with regional images (trained model), and (vii) the trained model accepting only classifications with ≥95% confidence. We compared species-specific results from alternative approaches to results from double review, which reduces the potential for misclassifications and was assumed to be the best approximation of truth. Despite high classification success, species-level misclassification rates for the base and trained models were sufficiently high to produce erroneous occupancy estimates and inferences related to space use across species. Increasing the confidence thresholds for image classification to 95% did not consistently improve performance. Classifying images as empty (or not) offered a reasonable approach to reduce effort (by 97.7%) and facilitated a semi-automated workflow that produced reliable estimates and inferences. Thus, camera-based monitoring combined with machine learning algorithms for image classification could facilitate monitoring with limited manual image classification.</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/rse2.356","usgsCitation":"Lonsinger, R.C., Dart, M.M., Larsen, R., and Knight, R.N., 2023, Efficacy of machine learning image classification for automated occupancy-based monitoring: Remote Sensing in Ecology and Conservation, v. 10, no. 1, p. 56-71, https://doi.org/10.1002/rse2.356.","productDescription":"16 p.","startPage":"56","endPage":"71","ipdsId":"IP-150309","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":442810,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/rse2.356","text":"Publisher Index Page"},{"id":432056,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Utah","otherGeospatial":"Dugway Proving Ground, Lund, Mojave Desert, Beaver Dam Wash, Colorado Plateau Great Basin 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T.","affiliations":[{"id":6681,"text":"Brigham Young University","active":true,"usgs":false}],"preferred":false,"id":907446,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Knight, Robert N.","contributorId":340677,"corporation":false,"usgs":false,"family":"Knight","given":"Robert","email":"","middleInitial":"N.","affiliations":[{"id":81648,"text":"US Army Dugway Proving Ground","active":true,"usgs":false}],"preferred":false,"id":907447,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70246549,"text":"sir20235075 - 2023 - Potential effects of projected pumping scenarios on future water-table elevations near Kirtland Air Force Base in Albuquerque, New Mexico","interactions":[],"lastModifiedDate":"2026-03-12T20:44:43.104195","indexId":"sir20235075","displayToPublicDate":"2023-07-10T12:38:28","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":"2023-5075","displayTitle":"Potential Effects of Projected Pumping Scenarios on Future Water-Table Elevations Near Kirtland Air Force Base in Albuquerque, New Mexico","title":"Potential effects of projected pumping scenarios on future water-table elevations near Kirtland Air Force Base in Albuquerque, New Mexico","docAbstract":"<p>The U.S. Geological Survey, in cooperation with the Air Force Civil Engineer Center, simulated different groundwater pumping scenarios from 2016 to 2050 to determine the potential future changes in groundwater levels in areas around the Kirtland Air Force Base Bulk Fuels Facility and an ethylene dibromide (EDB) plume. Projections of water supply and demand created by the Albuquerque Bernalillo County Water Utility Authority were used to develop the future groundwater pumping scenarios used as inputs for a refined local-scale model within the updated Middle Rio Grande Basin regional model.</p><p>The simulated water-table elevations in model cells that contain the EDB plume in the medium demand and medium supply scenario rose 29 feet (ft) until 2035, then remained within 10 ft of that elevation through 2050, whereas the water-table elevations in the high demand and low supply scenario rose about 26 ft until 2035 and then decreased by more than 10 ft. Simulated water-table elevations in the low demand and high supply scenario continued to rise throughout most of the future simulation period and peaked at about 44 ft over the 2016 water-table elevation. All of the scenarios ended the future simulation period with higher simulated water-table elevations than at the beginning of the future simulation period. Simulations that represented the potentially highest and lowest volume of groundwater pumping near the EDB plume by adjusting the spatial distribution of pumping had similar simulated water-table elevations as the nonadjusted scenarios, with maximum water-table elevation changes that only differed by about 2 ft from the nonadjusted scenarios. Consideration should be taken when using these model results to inform decisions because the model results are subject to uncertainty from many different sources, including uncertainty in the future pumping scenarios as well as the model itself because of the simplification of the hydrogeologic system.<br></p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235075","issn":"2328-0328","collaboration":"Prepared in cooperation with the Air Force Civil Engineer Center","usgsCitation":"Flickinger, A.K., 2023, Potential effects of projected pumping scenarios on future water-table elevations near Kirtland Air Force Base in Albuquerque, New Mexico: U.S. Geological Survey Scientific Investigations Report 2023–5075, 19 p., https://doi.org/10.3133/sir20235075.","productDescription":"Report: viii, 20 p.; Data Release","numberOfPages":"32","onlineOnly":"Y","ipdsId":"IP-139484","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":501039,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114964.htm","linkFileType":{"id":5,"text":"html"}},{"id":418777,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9ENV9EN","text":"USGS data release—Modified multi-node well (MNW2) files used to simulate potential future (2016-2050) water-table elevation change near Kirtland Air Force Base in Albuquerque, New Mexico"},{"id":418776,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5075/images"},{"id":418774,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5075/sir20235075.XML","size":"87.4 KB","linkFileType":{"id":8,"text":"xml"},"description":"SIR 2023-5075 XML"},{"id":418773,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5075/sir20235075.pdf","size":"1.86 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023-5075"},{"id":418772,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5075/coverthb.jpg"},{"id":418835,"rank":4,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20235075/full","description":"SIR 2023-5075 HTML"}],"country":"United States","state":"New Mexico","otherGeospatial":"Kirtland Air Force Base","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -107.3,\n              35.3\n            ],\n            [\n              -107.3,\n              34.3\n            ],\n            [\n              -106.0,\n              34.3\n            ],\n            [\n              -106.0,\n              35.3\n            ],\n            [\n              -107.3,\n              35.3\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","contact":"<p>Director, <a data-mce-href=\"h​ttps:/www​.usgs.gov/​centers/​nm-​water\" href=\"h​ttps:/www​.usgs.gov/​centers/​nm-​water\">New Mexico Water Science Center</a> <br>U.S. Geological Survey <br>6700 Edith Blvd. NE <br>Albuquerque, NM 87113</p><div class=\"elementToProof\"><a data-mce-href=\"../contact\" href=\"../contact\">Contact Pubs Warehouse</a></div>","tableOfContents":"<ul><li>Acknowledgments </li><li>Abstract</li><li>Introduction</li><li>Methods </li><li>Results of Simulations </li><li>Potential Effects of Simulated Future Pumping </li><li>Summary </li><li>References Cited</li></ul>","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"publishedDate":"2023-07-10","noUsgsAuthors":false,"publicationDate":"2023-07-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Flickinger, Allison K. 0000-0002-8638-2569 aflickinger@usgs.gov","orcid":"https://orcid.org/0000-0002-8638-2569","contributorId":193268,"corporation":false,"usgs":true,"family":"Flickinger","given":"Allison","email":"aflickinger@usgs.gov","middleInitial":"K.","affiliations":[],"preferred":true,"id":877125,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70247354,"text":"70247354 - 2023 - Stakeholder attitudes and perspectives on wildlife disease surveillance as a component of a One Health approach in Thailand","interactions":[],"lastModifiedDate":"2023-07-31T11:06:00.801819","indexId":"70247354","displayToPublicDate":"2023-07-10T12:10:52","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":10935,"text":"One Health Newsletter","active":true,"publicationSubtype":{"id":10}},"title":"Stakeholder attitudes and perspectives on wildlife disease surveillance as a component of a One Health approach in Thailand","docAbstract":"<p>Coordinated wildlife disease surveillance (WDS) can help professionals across disciplines effectively safeguard human, animal, and environmental health. The aims of this study were to understand how WDS in Thailand is utilized, valued, and can be improved within a One Health framework. An online questionnaire was distributed to 183 professionals (55.7% response rate) across Thailand working in wildlife, marine animal, livestock, domestic animal, zoo animal, environmental, and public health sectors. Twelve semi-structured interviews with key professionals were then performed. Three-quarters of survey respondents reported using WDS data and information. Sectors agreed upon ranking disease control (76.5% of respondents) as the most beneficial outcome of WDS, while fostering new ideas through collaboration was valued by few participants (2.0%). Accessing data collected by ones own sector was identified as the most challenging (50%) yet least difficult to improve (88.3%). Having legal authority to conduct WDS was the second most frequently identified challenge. Interviewees explained that legal documentation required for crossinstitutional collaborations posed a barrier to efficient communication and use of human resources. Survey respondents identified allocation of human resources (75.5%), adequate budget (71.6%), and having a clear communication system between sectors (71.6%) as highest priority areas for improvement to WDS in Thailand. Authorization from administrative officials and support from local community members were identified as challenges during in-person interviews. Future outreach should be directed towards these groups. As 42.9% of marine health professionals had difficulty knowing whom to contact in other sectors and 28.4% of survey respondents indicated that communication with marine health professionals was not applicable to their work, connecting the marine sector with other sectors may be prioritized. This study identifies priorities for addressing current challenges in the establishment of a general WDS system and information management system in Thailand while presenting a model for such evaluation in other regions.</p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.onehlt.2023.100600","usgsCitation":"George, S.E., Smink, M., Sangkachai, N., Wiratsudakul, A., Sakcamduang, W., Suwanpakdee, S., and Sleeman, J.M., 2023, Stakeholder attitudes and perspectives on wildlife disease surveillance as a component of a One Health approach in Thailand: One Health Newsletter, v. 17, 100600, 10 p., https://doi.org/10.1016/j.onehlt.2023.100600.","productDescription":"100600, 10 p.","ipdsId":"IP-154964","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":442811,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.onehlt.2023.100600","text":"Publisher Index 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Serena Elise","contributorId":317781,"corporation":false,"usgs":false,"family":"George","given":"Serena","email":"","middleInitial":"Elise","affiliations":[{"id":69152,"text":"University of Wisconsin-Madison, School of Veterinary Medicine","active":true,"usgs":false}],"preferred":false,"id":879297,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smink, Moniek","contributorId":317782,"corporation":false,"usgs":false,"family":"Smink","given":"Moniek","email":"","affiliations":[{"id":69153,"text":"University of Wisconsin-Madison, Department of Computer Sciences,","active":true,"usgs":false}],"preferred":false,"id":879298,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sangkachai, Nareerat","contributorId":317783,"corporation":false,"usgs":false,"family":"Sangkachai","given":"Nareerat","email":"","affiliations":[{"id":69154,"text":"Thailand National Wildlife Health Center, Faculty of Veterinary Science & The Monitoring and Surveillance Center for Zoonotic Diseases in Wildlife and Exotic Animals","active":true,"usgs":false}],"preferred":false,"id":879299,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wiratsudakul, Anuwat","contributorId":317784,"corporation":false,"usgs":false,"family":"Wiratsudakul","given":"Anuwat","email":"","affiliations":[{"id":69155,"text":"Thailand National Wildlife Health Center, Faculty of Veterinary Science, The Monitoring and Surveillance Center for Zoonotic Diseases in Wildlife and Exotic Animals & Department of Clinical Sciences and Public Health, Faculty of Veterinary Science","active":true,"usgs":false}],"preferred":false,"id":879300,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sakcamduang, Walasinee","contributorId":317785,"corporation":false,"usgs":false,"family":"Sakcamduang","given":"Walasinee","email":"","affiliations":[{"id":69156,"text":"Thailand National Wildlife Health Center, Faculty of Veterinary Science & Department of Clinical Sciences and Public Health, Faculty of Veterinary Science","active":true,"usgs":false}],"preferred":false,"id":879301,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Suwanpakdee, Sarin","contributorId":317786,"corporation":false,"usgs":false,"family":"Suwanpakdee","given":"Sarin","email":"","affiliations":[{"id":69155,"text":"Thailand National Wildlife Health Center, Faculty of Veterinary Science, The Monitoring and Surveillance Center for Zoonotic Diseases in Wildlife and Exotic Animals & Department of Clinical Sciences and Public Health, Faculty of Veterinary Science","active":true,"usgs":false}],"preferred":false,"id":879302,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Sleeman, Jonathan M. 0000-0002-9910-6125 jsleeman@usgs.gov","orcid":"https://orcid.org/0000-0002-9910-6125","contributorId":128,"corporation":false,"usgs":true,"family":"Sleeman","given":"Jonathan","email":"jsleeman@usgs.gov","middleInitial":"M.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true},{"id":82110,"text":"Midcontinent Regional Director's Office","active":true,"usgs":true}],"preferred":true,"id":879303,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70246625,"text":"70246625 - 2023 - BioLake: A first assessment of lake temperature-derived bioclimatic predictors for aquatic invasive species","interactions":[],"lastModifiedDate":"2023-07-12T12:15:02.02119","indexId":"70246625","displayToPublicDate":"2023-07-10T07:10:53","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":"BioLake: A first assessment of lake temperature-derived bioclimatic predictors for aquatic invasive species","docAbstract":"<div class=\"abstract-group  metis-abstract\"><div class=\"article-section__content en main\"><p>Aquatic invasive species (AIS) present major ecological and economic challenges globally, endangering ecosystems and human livelihoods. Managers and policy makers thus need tools to predict invasion risk and prioritize species and areas of concern, and they often use native range climate matching to determine whether a species could persist in a new location. However, climate matching for AIS often relies on air temperature rather than water temperature due to a lack of global water temperature data layers, and predictive power of models is seldom evaluated. We developed 12 global lake (water) temperature-derived “BioLake” bioclimatic layers for distribution modeling of aquatic species and compared “climatch” climate matching predictions (from climatchR package) from BioLake with those based on BioClim temperature layers and with a null model. We did this for 73 established AIS in the United States, training the models on their ranges outside of the United States and Canada. Models using either set of climate layers outperformed the null expectation by a similar (but modest) amount on average, but some species were occasionally found in locations with low climatch scores. Mean US climatch scores were higher for most species when using air temperature. Including additional climate layers in models reduced mean climatch scores, indicating that commonly used climatch score thresholds are not absolute but can be context specific and may require calibration based upon climate data used. Although finer resolution global lake temperature data would likely improve predictions, our BioLake layers provide a starting point for aquatic species distribution modeling. Climate matching was most effective for some species that originated at low latitudes or had small ranges. Climatch scores remain useful but limited for predicting AIS risk, perhaps because current ranges seldom fully reflect climatic tolerances (fundamental niches). Managers could consider climate matching as one of a suite of tools that can be used in AIS prioritization.</p></div></div>","language":"English","publisher":"Wiley","doi":"10.1002/ecs2.4616","usgsCitation":"Burner, R.C., Daniel, W., Engelstad, P.S., Churchill, C.J., and Erickson, R.A., 2023, BioLake: A first assessment of lake temperature-derived bioclimatic predictors for aquatic invasive species: Ecosphere, v. 14, no. 7, e4616, 15 p., https://doi.org/10.1002/ecs2.4616.","productDescription":"e4616, 15 p.","ipdsId":"IP-145073","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":442816,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.4616","text":"Publisher Index Page"},{"id":435259,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P96QLN5Y","text":"USGS data release","linkHelpText":"BioLake bioclimatic variables based on ERA5-Land lake temperature estimates 1991-2020"},{"id":435258,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9X2XEZL","text":"USGS data release","linkHelpText":"Calculations of BioLake climate data"},{"id":418893,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"14","issue":"7","noUsgsAuthors":false,"publicationDate":"2023-07-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Burner, Ryan C. 0000-0002-7314-9506","orcid":"https://orcid.org/0000-0002-7314-9506","contributorId":304152,"corporation":false,"usgs":true,"family":"Burner","given":"Ryan","email":"","middleInitial":"C.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":877422,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Daniel, Wesley 0000-0002-7656-8474","orcid":"https://orcid.org/0000-0002-7656-8474","contributorId":219312,"corporation":false,"usgs":true,"family":"Daniel","given":"Wesley","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":877423,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Engelstad, Peder S.","contributorId":316321,"corporation":false,"usgs":false,"family":"Engelstad","given":"Peder","email":"","middleInitial":"S.","affiliations":[{"id":68557,"text":"Natural Resource Ecology Laboratory, Colorado State University, Fort Collins, Colorado, USA","active":true,"usgs":false}],"preferred":false,"id":877424,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Churchill, Christopher J. 0000-0002-3227-3551 cchurchi@usgs.gov","orcid":"https://orcid.org/0000-0002-3227-3551","contributorId":4099,"corporation":false,"usgs":true,"family":"Churchill","given":"Christopher","email":"cchurchi@usgs.gov","middleInitial":"J.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":877425,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Erickson, Richard A. 0000-0003-4649-482X rerickson@usgs.gov","orcid":"https://orcid.org/0000-0003-4649-482X","contributorId":5455,"corporation":false,"usgs":true,"family":"Erickson","given":"Richard","email":"rerickson@usgs.gov","middleInitial":"A.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":877426,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70246801,"text":"70246801 - 2023 - Successful eradication of invasive American bullfrogs leads to coextirpation of emerging pathogens","interactions":[],"lastModifiedDate":"2023-10-23T14:50:27.703526","indexId":"70246801","displayToPublicDate":"2023-07-10T06:44:35","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1326,"text":"Conservation Letters","active":true,"publicationSubtype":{"id":10}},"title":"Successful eradication of invasive American bullfrogs leads to coextirpation of emerging pathogens","docAbstract":"<div class=\"abstract-group \"><div class=\"article-section__content en main\"><p>Interventions of the host–pathogen dynamics provide strong tests of relationships, yet they are still rarely applied across multiple populations. After American bullfrogs (<i>Rana catesbeiana</i>) invaded a wildlife refuge where federally threatened Chiricahua leopard frogs (<i>R. chiricahuensis</i>) were reintroduced 12 years prior, managers launched a landscape-scale eradication effort to help ensure continued recovery of the native species. We used a before-after-control-impact design and environmental DNA sampling of 19 eradication sites and 18 control sites between fall 2016 and winter 2020–2021 to measure community-level responses to bullfrog eradication, including for two pathogens. Dynamic occupancy models revealed successful eradication from 94% of treatment sites. Native amphibians did not respond to bullfrog eradication, but the pathogens amphibian chytrid fungus (<i>Batrachochytrium dendrobatidis</i>) and ranaviruses were coextirpated with bullfrogs. Our spatially replicated experimental approach provides strong evidence that management of invasive species can simultaneously reduce predation and disease risk for imperiled species.</p></div></div>","language":"English","publisher":"Wiley","doi":"10.1111/conl.12970","usgsCitation":"Hossack, B., Hall, D.L., Crawford, C.L., Goldberg, C.S., Muths, E., Sigafus, B., and Chambert, T., 2023, Successful eradication of invasive American bullfrogs leads to coextirpation of emerging pathogens: Conservation Letters, v. 16, e12970, 9 p., https://doi.org/10.1111/conl.12970.","productDescription":"e12970, 9 p.","ipdsId":"IP-148643","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":442820,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/conl.12970","text":"Publisher Index Page"},{"id":419142,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -112.09766862673155,\n              32.32879233910836\n            ],\n            [\n              -112.09766862673155,\n              31.321102431216232\n            ],\n            [\n              -111.0104885999884,\n              31.321102431216232\n            ],\n            [\n              -111.0104885999884,\n              32.32879233910836\n            ],\n            [\n              -112.09766862673155,\n              32.32879233910836\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"16","noUsgsAuthors":false,"publicationDate":"2023-07-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Hossack, Blake R. 0000-0001-7456-9564","orcid":"https://orcid.org/0000-0001-7456-9564","contributorId":229347,"corporation":false,"usgs":true,"family":"Hossack","given":"Blake R.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":878320,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hall, David L.","contributorId":222395,"corporation":false,"usgs":false,"family":"Hall","given":"David","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":878321,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Crawford, Catherine L.","contributorId":191976,"corporation":false,"usgs":false,"family":"Crawford","given":"Catherine","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":878322,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Goldberg, Caren S.","contributorId":76879,"corporation":false,"usgs":false,"family":"Goldberg","given":"Caren","email":"","middleInitial":"S.","affiliations":[{"id":5132,"text":"Washington State University, Pullman","active":true,"usgs":false}],"preferred":false,"id":878323,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Muths, Erin L. 0000-0002-5498-3132","orcid":"https://orcid.org/0000-0002-5498-3132","contributorId":245922,"corporation":false,"usgs":true,"family":"Muths","given":"Erin L.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":878324,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sigafus, Brent H. 0000-0002-7422-8927","orcid":"https://orcid.org/0000-0002-7422-8927","contributorId":264740,"corporation":false,"usgs":true,"family":"Sigafus","given":"Brent H.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":878325,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Chambert, Thierry 0000-0002-9450-9080 tchambert@usgs.gov","orcid":"https://orcid.org/0000-0002-9450-9080","contributorId":191979,"corporation":false,"usgs":false,"family":"Chambert","given":"Thierry","email":"tchambert@usgs.gov","affiliations":[],"preferred":false,"id":878326,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70249566,"text":"70249566 - 2023 - Predicting inundation dynamics and hydroperiods of small, isolated wetlands using a machine learning approach","interactions":[],"lastModifiedDate":"2023-10-17T11:48:16.544061","indexId":"70249566","displayToPublicDate":"2023-07-10T06:42:21","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3750,"text":"Wetlands","onlineIssn":"1943-6246","printIssn":"0277-5212","active":true,"publicationSubtype":{"id":10}},"title":"Predicting inundation dynamics and hydroperiods of small, isolated wetlands using a machine learning approach","docAbstract":"<div id=\"Abs1-section\" class=\"c-article-section\"><div id=\"Abs1-content\" class=\"c-article-section__content\"><p>The duration of inundation or saturation (i.e., hydroperiod) controls many wetland functions. In particular, it is a key determinant of whether a wetland will provide suitable breeding habitat for amphibians and other taxa that often have specific hydrologic requirements. Yet, scientists and land managers often are challenged by a lack of sufficient monitoring data to enable the understanding of the wetting and drying dynamics of small depressional wetlands. In this study, we present and evaluate an approach to predict daily inundation dynamics using a large wetland water-level dataset and a random forest algorithm. We relied on predictor variables that described characteristics of basin morphology of each wetland and atmospheric water budget estimates over various antecedent periods. These predictor variables were derived from datasets available over the conterminous United States making this approach potentially extendable to other locations. Model performance was evaluated using two metrics, median hydroperiod and the proportion of correctly classified days. We found that models performed well overall with a median balanced accuracy of 83% on validation data. Median hydroperiod was predicted most accurately for wetlands that were infrequently inundated and least accurate for permanent wetlands. The proportion of inundated days was predicted most accurately in permanent wetlands (99%) followed by frequently inundated wetlands (98%) and infrequently inundated wetlands (93%). This modeling approach provided accurate estimates of inundation and could be useful in other depressional wetlands where the primary water flux occurs with the atmosphere and basin morphology is a critical control on wetland inundation and hydroperiods.</p></div></div>","language":"English","publisher":"Springer","doi":"10.1007/s13157-023-01706-2","usgsCitation":"Riley, J.W., and Stillwell, C.C., 2023, Predicting inundation dynamics and hydroperiods of small, isolated wetlands using a machine learning approach: Wetlands, v. 43, 63, 17 p., https://doi.org/10.1007/s13157-023-01706-2.","productDescription":"63, 17 p.","ipdsId":"IP-140298","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":442823,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s13157-023-01706-2","text":"Publisher Index Page"},{"id":421936,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -84.4899373474849,\n              30.03362023784058\n            ],\n            [\n              -84.4899373474849,\n              29.881324089510343\n            ],\n            [\n              -84.31415609748471,\n              29.881324089510343\n            ],\n            [\n              -84.31415609748471,\n              30.03362023784058\n            ],\n            [\n              -84.4899373474849,\n              30.03362023784058\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"43","noUsgsAuthors":false,"publicationDate":"2023-07-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Riley, Jeffrey W. 0000-0001-5525-3134 jriley@usgs.gov","orcid":"https://orcid.org/0000-0001-5525-3134","contributorId":3605,"corporation":false,"usgs":true,"family":"Riley","given":"Jeffrey","email":"jriley@usgs.gov","middleInitial":"W.","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":886250,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stillwell, Charles C. 0000-0002-4571-4897","orcid":"https://orcid.org/0000-0002-4571-4897","contributorId":270394,"corporation":false,"usgs":true,"family":"Stillwell","given":"Charles","email":"","middleInitial":"C.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":886251,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70246736,"text":"70246736 - 2023 - Impacts of spontaneous waterfall development on bedrock river longitudinal profile morphology","interactions":[],"lastModifiedDate":"2023-07-18T11:42:28.382798","indexId":"70246736","displayToPublicDate":"2023-07-08T06:40:06","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":6454,"text":"Journal of Geophysical Research - Earth Surface","active":true,"publicationSubtype":{"id":10}},"title":"Impacts of spontaneous waterfall development on bedrock river longitudinal profile morphology","docAbstract":"<div class=\"article-section__content en main\"><p>River profiles are shaped by climatic and tectonic history, lithology, and internal feedbacks between flow hydraulics, sediment transport and erosion. In steep channels, waterfalls may self-form without changes in external forcing (i.e., autogenic formation) and erode at rates faster or slower than an equivalent channel without waterfalls. We use a 1-D numerical model to investigate how self-formed waterfalls alter the morphology of bedrock river longitudinal profiles. We modify the standard stream power model to include a slope threshold above which waterfalls spontaneously form and a rate constant allowing waterfalls to erode faster or slower than other fluvial processes. Using this model, we explore how waterfall formation alters both steady state and transient longitudinal profile forms. Our model predicts that fast waterfalls create km-scale reaches in a dynamic equilibrium with channel slope held approximately constant at the threshold slope for waterfall formation, while slow waterfalls can create local channel slope maxima at the location of slow waterfall development. Furthermore, slow waterfall profiles integrate past base level histories, leading to multiple possible profile forms, even at steady-state. Consistency between our model predictions and field observations of waterfall-rich rivers in the Kings and Kaweah drainages in the southern Sierra Nevada, California, supports the hypothesis that waterfall formation can modulate river profiles in nature. Our findings may help identify how bedrock channels are influenced by waterfall erosion and aid in distinguishing between signatures of external and internal perturbations, thereby strengthening our ability to interpret past climate and tectonic changes from river longitudinal profiles.</p></div>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2022JF007057","usgsCitation":"Rothman, S.D., Scheingross, J.S., McCoy, S.W., and Dow, H.W., 2023, Impacts of spontaneous waterfall development on bedrock river longitudinal profile morphology: Journal of Geophysical Research - Earth Surface, v. 128, no. 7, e2022JF007057, https://doi.org/10.1029/2022JF007057.","productDescription":"e2022JF007057","ipdsId":"IP-150889","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":442825,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2022jf007057","text":"Publisher Index Page"},{"id":419038,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"128","issue":"7","noUsgsAuthors":false,"publicationDate":"2023-07-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Rothman, Sophie D.","contributorId":316720,"corporation":false,"usgs":false,"family":"Rothman","given":"Sophie","email":"","middleInitial":"D.","affiliations":[{"id":12742,"text":"University of Nevada Reno","active":true,"usgs":false}],"preferred":false,"id":878128,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Scheingross, Joel S.","contributorId":316721,"corporation":false,"usgs":false,"family":"Scheingross","given":"Joel","email":"","middleInitial":"S.","affiliations":[{"id":12742,"text":"University of Nevada Reno","active":true,"usgs":false}],"preferred":false,"id":878129,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McCoy, Scott W.","contributorId":316722,"corporation":false,"usgs":false,"family":"McCoy","given":"Scott","email":"","middleInitial":"W.","affiliations":[{"id":12742,"text":"University of Nevada Reno","active":true,"usgs":false}],"preferred":false,"id":878130,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dow, Helen Willemien 0000-0001-6386-5560","orcid":"https://orcid.org/0000-0001-6386-5560","contributorId":299290,"corporation":false,"usgs":true,"family":"Dow","given":"Helen","email":"","middleInitial":"Willemien","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":878131,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70246554,"text":"70246554 - 2023 - Postfire hydrologic response along the central California (USA) coast: Insights for the emergency assessment of postfire debris-flow hazards","interactions":[],"lastModifiedDate":"2023-10-23T14:41:47.420879","indexId":"70246554","displayToPublicDate":"2023-07-07T09:56:56","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2604,"text":"Landslides","active":true,"publicationSubtype":{"id":10}},"title":"Postfire hydrologic response along the central California (USA) coast: Insights for the emergency assessment of postfire debris-flow hazards","docAbstract":"<p><span>The steep, tectonically active terrain along the Central California (USA) coast is well known to produce deadly and destructive debris flows. However, the extent to which fire affects debris-flow susceptibility in this region is an open question. We documented the occurrence of postfire debris floods and flows following the landfall of a storm that delivered intense rainfall across multiple burn areas. We used this inventory to evaluate the predictive performance of the US Geological Survey M1 likelihood model, a tool that presently underlies the emergency assessment of postfire debris-flow hazards in the western USA. To test model performance, we used the threat score skill statistic and found that the rainfall thresholds estimated by the M1 model for the Central California coast performed similarly to training (Southern California) and testing (Intermountain West) data associated with the original model calibration. Model performance decreased when differentiating between “minor” and “major” postfire hydrologic response types, which weigh effects on human life and infrastructure. Our results underscore that the problem of false positives is a major challenge for developing accurate rainfall thresholds for the occurrence of postfire debris flows. As wildfire activity increases throughout the western USA, so too will the demand for the assessment of postfire debris-flow hazards. We conclude that additional collection of field-verified inventories of postfire hydrologic response will be critical to prioritize which model variables may be suitable candidates for regional calibration or replacement.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s10346-023-02106-7","usgsCitation":"Thomas, M.A., Kean, J.W., McCoy, S., Lindsay, D.N., Kostelnik, J., Cavagnaro, D.B., Rengers, F.K., East, A.E., Schwartz, J., Smith, D.P., and Collins, B.D., 2023, Postfire hydrologic response along the central California (USA) coast: Insights for the emergency assessment of postfire debris-flow hazards: Landslides, v. 20, p. 2421-2436, https://doi.org/10.1007/s10346-023-02106-7.","productDescription":"16 p.","startPage":"2421","endPage":"2436","ipdsId":"IP-139528","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":442830,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10346-023-02106-7","text":"Publisher Index Page"},{"id":435262,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P91O03Y7","text":"USGS data release","linkHelpText":"Field-verified inventory of postfire hydrologic response for the 2020 CZU Lightning Complex, River, Camel, and Dolan Fires following a 26-29 January 2021 atmospheric river storm sequence"},{"id":418804,"rank":1,"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              -121.47368381570269,\n              35.81897449008355\n            ],\n            [\n              -120.78708136085193,\n              36.2836437903476\n            ],\n            [\n              -121.84398626326276,\n              37.24464732874951\n            ],\n            [\n              -122.37243871446816,\n              36.97394608796073\n            ],\n            [\n              -121.47368381570269,\n              35.81897449008355\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"20","noUsgsAuthors":false,"publicationDate":"2023-07-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Thomas, Matthew A. 0000-0002-9828-5539 matthewthomas@usgs.gov","orcid":"https://orcid.org/0000-0002-9828-5539","contributorId":200616,"corporation":false,"usgs":true,"family":"Thomas","given":"Matthew","email":"matthewthomas@usgs.gov","middleInitial":"A.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":877143,"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":877144,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McCoy, Scott W.","contributorId":267182,"corporation":false,"usgs":false,"family":"McCoy","given":"Scott W.","affiliations":[{"id":16686,"text":"University of Nevada, Reno","active":true,"usgs":false}],"preferred":false,"id":877145,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lindsay, Donald N.","contributorId":216337,"corporation":false,"usgs":false,"family":"Lindsay","given":"Donald","email":"","middleInitial":"N.","affiliations":[{"id":12640,"text":"California Geological Survey","active":true,"usgs":false}],"preferred":false,"id":877146,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kostelnik, Jaime 0000-0002-1817-5461","orcid":"https://orcid.org/0000-0002-1817-5461","contributorId":300717,"corporation":false,"usgs":true,"family":"Kostelnik","given":"Jaime","email":"","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":877147,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cavagnaro, David B.","contributorId":267181,"corporation":false,"usgs":false,"family":"Cavagnaro","given":"David","email":"","middleInitial":"B.","affiliations":[{"id":16686,"text":"University of Nevada, Reno","active":true,"usgs":false}],"preferred":false,"id":877148,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"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":877149,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"East, Amy E. 0000-0002-9567-9460 aeast@usgs.gov","orcid":"https://orcid.org/0000-0002-9567-9460","contributorId":196364,"corporation":false,"usgs":true,"family":"East","given":"Amy","email":"aeast@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":877150,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Schwartz, Jonathan","contributorId":312505,"corporation":false,"usgs":false,"family":"Schwartz","given":"Jonathan","email":"","affiliations":[{"id":37389,"text":"U.S. Forest Service","active":true,"usgs":false}],"preferred":false,"id":877151,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Smith, Douglas P.","contributorId":201716,"corporation":false,"usgs":false,"family":"Smith","given":"Douglas","email":"","middleInitial":"P.","affiliations":[{"id":35924,"text":"California State University, Monterey Bay","active":true,"usgs":false}],"preferred":false,"id":877152,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Collins, Brian D. 0000-0003-4881-5359 bcollins@usgs.gov","orcid":"https://orcid.org/0000-0003-4881-5359","contributorId":149278,"corporation":false,"usgs":true,"family":"Collins","given":"Brian","email":"bcollins@usgs.gov","middleInitial":"D.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":877153,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}}
,{"id":70246596,"text":"70246596 - 2023 - Translating stakeholder narratives for participatory modeling in landscape ecology","interactions":[],"lastModifiedDate":"2023-09-06T16:23:41.955537","indexId":"70246596","displayToPublicDate":"2023-07-07T06:57:50","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":"Translating stakeholder narratives for participatory modeling in landscape ecology","docAbstract":"<h3 class=\"c-article__sub-heading\" data-test=\"abstract-sub-heading\">Context</h3><p>Engaging stakeholders in research is needed for many of the sustainability challenges that landscape ecologists address. Involving stakeholders’ perspectives through narratives in participatory modeling fosters better understanding of the problem and evaluation of the acceptability of tradeoffs and creates buy-in for management actions. However, stakeholder-driven inputs often take the form of complex qualitative descriptions, rather than model-ready numerical or categorical inputs.</p><h3 class=\"c-article__sub-heading\" data-test=\"abstract-sub-heading\">Objectives</h3><p>Translating narratives into models, model parameters, or scenarios is essential for leveraging stakeholder knowledge and engagement. Drawing from varied experiences to identify lessons learned and pitfalls, we address the practice of translating narratives into models and using those narratives to interpret and communicate results.</p><h3 class=\"c-article__sub-heading\" data-test=\"abstract-sub-heading\">Methods</h3><p>We drew from seven participatory landscape ecology projects across North America to synthesize lessons for the inclusion of stakeholder narratives in modeling studies.</p><h3 class=\"c-article__sub-heading\" data-test=\"abstract-sub-heading\">Results</h3><p>We offer 8 lessons as practical guidance for other landscape ecologists to move the science beyond a unilateral focus on ecological systems and to maximize the benefits of landscape sustainability science.</p><h3 class=\"c-article__sub-heading\" data-test=\"abstract-sub-heading\">Conclusions</h3><p>These lessons are starting points, as real projects are complex, nuanced, and sometimes contradictory. Translating narratives into models is important for addressing complex sustainability challenges; we hope that these starting points are helpful to those foraying into this type of research.</p>","language":"English","publisher":"Springer","doi":"10.1007/s10980-023-01724-9","usgsCitation":"Vukomanovic, J., Smart, L., Koch, J., Dale, V., Plassin, S., Byrd, K.B., Beier, C., and Doyon, F., 2023, Translating stakeholder narratives for participatory modeling in landscape ecology: Landscape Ecology, v. 38, p. 2453-2474, https://doi.org/10.1007/s10980-023-01724-9.","productDescription":"22 p.","startPage":"2453","endPage":"2474","ipdsId":"IP-136700","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":502612,"rank":2,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://research.wur.nl/en/publications/translating-stakeholder-narratives-for-participatory-modeling-in-","text":"External Repository"},{"id":418854,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"38","noUsgsAuthors":false,"publicationDate":"2023-07-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Vukomanovic, Jelena","contributorId":316275,"corporation":false,"usgs":false,"family":"Vukomanovic","given":"Jelena","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":877297,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smart, Lindsey","contributorId":316276,"corporation":false,"usgs":false,"family":"Smart","given":"Lindsey","affiliations":[{"id":68543,"text":"North Carolina State University, The Nature Conservancy","active":true,"usgs":false}],"preferred":false,"id":877298,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Koch, Jennifer","contributorId":316277,"corporation":false,"usgs":false,"family":"Koch","given":"Jennifer","affiliations":[{"id":7062,"text":"University of Oklahoma","active":true,"usgs":false}],"preferred":false,"id":877299,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dale, Virginia","contributorId":316278,"corporation":false,"usgs":false,"family":"Dale","given":"Virginia","email":"","affiliations":[{"id":12716,"text":"University of Tennessee","active":true,"usgs":false}],"preferred":false,"id":877300,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Plassin, Sophie","contributorId":316279,"corporation":false,"usgs":false,"family":"Plassin","given":"Sophie","email":"","affiliations":[{"id":34610,"text":"Universite de Toulouse","active":true,"usgs":false}],"preferred":false,"id":877301,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Byrd, Kristin B. 0000-0002-5725-7486 kbyrd@usgs.gov","orcid":"https://orcid.org/0000-0002-5725-7486","contributorId":3814,"corporation":false,"usgs":true,"family":"Byrd","given":"Kristin","email":"kbyrd@usgs.gov","middleInitial":"B.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":877302,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Beier, Colin","contributorId":316280,"corporation":false,"usgs":false,"family":"Beier","given":"Colin","affiliations":[{"id":37519,"text":"SUNY College of Environmental Science and Forestry","active":true,"usgs":false}],"preferred":false,"id":877303,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Doyon, Frederik","contributorId":316282,"corporation":false,"usgs":false,"family":"Doyon","given":"Frederik","email":"","affiliations":[{"id":68544,"text":"Institut des sciences de la foret temperee, Universite du Quebec","active":true,"usgs":false}],"preferred":false,"id":877304,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70246616,"text":"70246616 - 2023 - A detailed view of the 2020-2023 southwestern Puerto Rico seismic sequence with deep learning","interactions":[],"lastModifiedDate":"2023-12-04T16:59:36.832347","indexId":"70246616","displayToPublicDate":"2023-07-06T08:36:24","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 detailed view of the 2020-2023 southwestern Puerto Rico seismic sequence with deep learning","docAbstract":"<p><span>The 2020–2023 southwestern Puerto Rico seismic sequence, still ongoing in 2023, is remarkable for its multiple‐fault rupture complexity and elevated aftershock productivity. We applied an automatic workflow to continuous data from 43 seismic stations in Puerto Rico to build an enhanced earthquake catalog with ∼180,000 events for the 3+ yr sequence from 28 December 2019 to 1 January 2023. This workflow contained the EQTransformer (EQT) deep learning model for event detection and phase picking, the EikoNet‐Hypocenter Inversion with Stein Variational Inference probabilistic earthquake location approach with a neural network trained to solve the eikonal wave equation, and relocation with event‐pair waveform cross correlation. EQT increased the number of catalog events in the sequence by about seven times, though its performance was not quite as good as thorough analyst review. The enhanced catalog revealed new structural details of the sequence space–time evolution, including sudden changes in activity, on a complex system of many small normal and strike‐slip faults. This sequence started on 28 December 2019 with an M&nbsp;4.7 strike‐slip earthquake followed by 10&nbsp;days of shallow strike‐slip foreshocks, including several M&nbsp;5+ earthquakes, in a compact region. The oblique normal fault&nbsp;</span><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><span id=\"MathJax-Span-2\" class=\"mrow\"><span id=\"MathJax-Span-3\" class=\"msub\"><strong><i><span id=\"MathJax-Span-4\" class=\"mi\">M</span></i></strong><sub><span id=\"MathJax-Span-5\" class=\"mi\">w</span></sub></span></span></span></span></span></span><span>&nbsp;6.4 mainshock then happened on 7 January 2020. Early aftershocks in January 2020, with several M&nbsp;5+ earthquakes, quickly expanded into two intersecting fault zones with diffuse seismicity: one extending ∼35&nbsp;km on a northward‐dipping normal fault and the other ∼60‐km‐long and oriented west‐northwest–east‐southeast on strike‐slip faults. Months to years later, aftershocks moved westward, deeper, and to outer reaches of the active fault zones, with abrupt rapid seismicity migration following larger M&nbsp;4.7+ aftershocks in May, July, and December 2020. The observed seismicity evolution indicates cascading failure from stress transfer on multiple critically stressed faults. High aftershock productivity results from the complex multiple‐fault network hosting the sequence, which is characteristic of an immature fault system in the diffuse deformation zone around Puerto Rico, at the complicated North American–Caribbean plate boundary region.</span></p>","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120220229","usgsCitation":"Yoon, C., Cochran, E.S., Vanacore, E.A., Huerfano, V., Baez-Sanchez, G., Wilding, J.D., and Smith, J., 2023, A detailed view of the 2020-2023 southwestern Puerto Rico seismic sequence with deep learning: Bulletin of the Seismological Society of America, v. 113, no. 6, p. 2377-2415, https://doi.org/10.1785/0120220229.","productDescription":"39 p.","startPage":"2377","endPage":"2415","ipdsId":"IP-146771","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":418860,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Puerto Rico","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -67.32164133530259,\n              18.326886647205086\n            ],\n            [\n              -67.32164133530259,\n              17.87971493886245\n            ],\n            [\n              -66.37514979104056,\n              17.87971493886245\n            ],\n            [\n              -66.37514979104056,\n              18.326886647205086\n            ],\n            [\n              -67.32164133530259,\n              18.326886647205086\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"113","issue":"6","noUsgsAuthors":false,"publicationDate":"2023-07-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Yoon, Clara 0000-0003-4521-3889","orcid":"https://orcid.org/0000-0003-4521-3889","contributorId":222019,"corporation":false,"usgs":true,"family":"Yoon","given":"Clara","email":"","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":877384,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cochran, Elizabeth S. 0000-0003-2485-4484 ecochran@usgs.gov","orcid":"https://orcid.org/0000-0003-2485-4484","contributorId":2025,"corporation":false,"usgs":true,"family":"Cochran","given":"Elizabeth","email":"ecochran@usgs.gov","middleInitial":"S.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":877385,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Vanacore, Elizabeth A.","contributorId":316311,"corporation":false,"usgs":false,"family":"Vanacore","given":"Elizabeth","email":"","middleInitial":"A.","affiliations":[{"id":62735,"text":"University of Puerto Rico Mayagüez","active":true,"usgs":false}],"preferred":false,"id":877386,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Huerfano, Victor","contributorId":316312,"corporation":false,"usgs":false,"family":"Huerfano","given":"Victor","email":"","affiliations":[{"id":62735,"text":"University of Puerto Rico Mayagüez","active":true,"usgs":false}],"preferred":false,"id":877387,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Baez-Sanchez, Gisela","contributorId":316313,"corporation":false,"usgs":false,"family":"Baez-Sanchez","given":"Gisela","email":"","affiliations":[{"id":62735,"text":"University of Puerto Rico Mayagüez","active":true,"usgs":false}],"preferred":false,"id":877388,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wilding, John D.","contributorId":316320,"corporation":false,"usgs":false,"family":"Wilding","given":"John","email":"","middleInitial":"D.","affiliations":[{"id":13711,"text":"Caltech","active":true,"usgs":false}],"preferred":false,"id":877389,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Smith, Jonathan D.","contributorId":239737,"corporation":false,"usgs":false,"family":"Smith","given":"Jonathan D.","affiliations":[],"preferred":false,"id":877390,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70246663,"text":"70246663 - 2023 - Structural discontinuities and their control on hydrothermal systems in the Great Basin, USA","interactions":[],"lastModifiedDate":"2023-07-13T12:09:02.95183","indexId":"70246663","displayToPublicDate":"2023-07-06T07:05:00","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":16300,"text":"Geoenergy","active":true,"publicationSubtype":{"id":10}},"title":"Structural discontinuities and their control on hydrothermal systems in the Great Basin, USA","docAbstract":"<p>Faults are important controls on hydrothermal circulation worldwide. More specifically, structural discontinuities, i.e. locations where faults interact and intersect, host many hydrothermal systems. In the Great Basin, western USA, an extensive characterization effort demonstrated that hydrothermal systems are controlled by one (or more) of eight types of structural discontinuities. Presumably, specific attributes of these structural settings control the generation and maintenance of permeability and porosity, and therefore localize hydrothermal processes. Herein, I examine representative examples of the eight structural settings that host hydrothermal systems in the Great Basin. For each setting, I use a boundary element method to model fault slip on the major faults and track the distribution of stress and strain in the surrounding crust. Results demonstrate that the largest magnitude and most localized stress and strain effects occur in the structural settings that host the largest number of hydrothermal systems; fault stepovers and fault terminations. Structural settings that are common in areas of strike-slip faulting also show localized stress and strain effects. The modelling presented provides process-based explanations for the empirical and conceptual results of regional characterization of Great Basin hydrothermal systems.</p>","language":"English","publisher":"Geological Society of London","doi":"10.1144/geoenergy2023-009","usgsCitation":"Siler, D.L., 2023, Structural discontinuities and their control on hydrothermal systems in the Great Basin, USA: Geoenergy, v. 1, no. 1, 10 p., https://doi.org/10.1144/geoenergy2023-009.","productDescription":"10 p.","ipdsId":"IP-146721","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":442846,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1144/geoenergy2023-009","text":"Publisher Index Page"},{"id":435264,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9S73O5C","text":"USGS data release","linkHelpText":"Stress transfer modeling of Great Basin, USA structural discontinuities; Data and MATLAB functions (ver. 1.1, June 2023)"},{"id":418922,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Great Basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -120.971198043698,\n              43.70678410718071\n            ],\n            [\n              -120.971198043698,\n              33.361880330157675\n            ],\n            [\n              -107.7054053941411,\n              33.361880330157675\n            ],\n            [\n              -107.7054053941411,\n              43.70678410718071\n            ],\n            [\n              -120.971198043698,\n              43.70678410718071\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"1","issue":"1","noUsgsAuthors":false,"publicationDate":"2023-07-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Siler, Drew L. 0000-0001-7540-8244","orcid":"https://orcid.org/0000-0001-7540-8244","contributorId":203341,"corporation":false,"usgs":true,"family":"Siler","given":"Drew","email":"","middleInitial":"L.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":877837,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70255560,"text":"70255560 - 2023 - Beyond simple trend tests: Detecting significant changes in design-flood quantiles","interactions":[],"lastModifiedDate":"2024-06-24T11:48:57.352622","indexId":"70255560","displayToPublicDate":"2023-07-06T06:40:08","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Beyond simple trend tests: Detecting significant changes in design-flood quantiles","docAbstract":"<div class=\"article-section__content en main\"><p>Changes in annual maximum flood (AMF), which are usually detected using simple trend tests (e.g., Mann-Kendall test (MKT)), are expected to change design-flood estimates. We propose an alternate framework to detect significant changes in design-flood between two periods and evaluate it for synthetically generated AMF from the Log-Pearson Type-3 (LP3) distribution due to changes in moments associated with flood distribution. Synthetic experiments show MKT does not consider changes in all three moments of the LP3 distribution and incorrectly detects changes in design-flood. We applied the framework on 31 river basins spread across the United States. Statistically significant changes in design-flood quantiles were observed even without a significant trend in AMF and basins with statistically significant trend did not necessarily exhibit statistically significant changes in design-flood. We recommend application of the framework for evaluating changes in design-flood estimates considering changes in all the moments as opposed to simple trend tests.</p></div>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2023GL103438","usgsCitation":"Awasthi, C., Archfield, S.A., Reich, B.J., and Sankarasubramanian, A., 2023, Beyond simple trend tests: Detecting significant changes in design-flood quantiles: Geophysical Research Letters, v. 50, no. 13, e2023GL103438, 11 p., https://doi.org/10.1029/2023GL103438.","productDescription":"e2023GL103438, 11 p.","ipdsId":"IP-147071","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":442852,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2023gl103438","text":"Publisher Index Page"},{"id":430444,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"50","issue":"13","noUsgsAuthors":false,"publicationDate":"2023-07-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Awasthi, Chandramauli 0000-0001-9826-5231","orcid":"https://orcid.org/0000-0001-9826-5231","contributorId":298942,"corporation":false,"usgs":false,"family":"Awasthi","given":"Chandramauli","email":"","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":904672,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Archfield, Stacey A. 0000-0002-9011-3871 sarch@usgs.gov","orcid":"https://orcid.org/0000-0002-9011-3871","contributorId":1874,"corporation":false,"usgs":true,"family":"Archfield","given":"Stacey","email":"sarch@usgs.gov","middleInitial":"A.","affiliations":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":904673,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Reich, Brian J.","contributorId":150871,"corporation":false,"usgs":false,"family":"Reich","given":"Brian","email":"","middleInitial":"J.","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":904674,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sankarasubramanian, Arumugam","contributorId":339554,"corporation":false,"usgs":false,"family":"Sankarasubramanian","given":"Arumugam","email":"","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":904675,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
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