{"pageNumber":"123","pageRowStart":"3050","pageSize":"25","recordCount":40783,"records":[{"id":70246580,"text":"70246580 - 2023 - Spatial variability in vertical accretion and carbon sequestration in salt marsh soils of an urban estuary","interactions":[],"lastModifiedDate":"2023-07-12T10:52:50.782645","indexId":"70246580","displayToPublicDate":"2023-05-17T08:13:28","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":"Spatial variability in vertical accretion and carbon sequestration in salt marsh soils of an urban estuary","docAbstract":"<p><span>Salt marshes in New York City’s Jamaica Bay have been disappearing and deteriorating since early 1900s, resulting in the loss of long-term accumulated carbon storage. However, the spatial variations and mechanisms in vertical accretion and soil organic carbon (SOC) sequestration across this highly urbanized estuary remains unclear. In this study, we collected soil cores to a depth of ~ 50&nbsp;cm across Jamaica Bay to study the spatial variability in long-term (50–100 years) vertical accretion, the accumulation of mineral sediment and organic matter, and SOC sequestration. Results of gamma spectrometry analysis of&nbsp;</span><sup>137</sup><span>Cs and&nbsp;</span><sup>210</sup><span>Pb show that there was moderate spatial variability in long-term vertical accretion rates across Jamaica Bay study sites (mean: 0.48 ± 0.13&nbsp;cm yr</span><sup>− 1</sup><span>, range: 0.36–0.78&nbsp;cm yr</span><sup>− 1</sup><span>). This local scale spatial variability in vertical accretion is largely driven by spatial variations of sedimentation. The magnitude of the long-term vertical accretion in Jamaica Bay is significantly correlated with organic matter accumulation, but not with mineral sediment. However, the role of organic matter in contributing to vertical accretion has been declining. The declining role of organic matter to vertical accretion is reflected by the lower SOC sequestration rate (mean: 128 and range: 26–189&nbsp;g C m</span><sup>− 2</sup><span>&nbsp;yr</span><sup>− 1</sup><span>&nbsp;using the&nbsp;</span><sup>210</sup><span>Pb dating technique) compared to the global mean salt marsh SOC sequestration rate (244&nbsp;g C m</span><sup>− 2</sup><span>&nbsp;yr</span><sup>− 1</sup><span>). This is especially so on the marsh islands in the degrading western part of the bay where SOC sequestration was less than half the global average.</span></p>","language":"English","publisher":"Springer Nature","doi":"10.1007/s13157-023-01699-y","usgsCitation":"Wang, H., Snedden, G., Hartig, E., and Chen, Q., 2023, Spatial variability in vertical accretion and carbon sequestration in salt marsh soils of an urban estuary: Wetlands, v. 43, no. 5, 49, 16 p.; Data Release, https://doi.org/10.1007/s13157-023-01699-y.","productDescription":"49, 16 p.; Data Release","ipdsId":"IP-147054","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":418859,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":418858,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9XQBYXU","text":"Soil property and geochronology (137Cs and 210Pb) data (2014) in salt marsh soils of Jamaica Bay Estuary, New York City"}],"country":"United States","state":"New York","city":"New York City","otherGeospatial":"Jamaica Bay","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -73.9351951637045,\n              40.55401609118147\n            ],\n            [\n              -73.76456876917054,\n              40.59793722111755\n            ],\n            [\n              -73.73117649148077,\n              40.6337950544268\n            ],\n            [\n              -73.7409498410488,\n              40.65326150244678\n            ],\n            [\n              -73.75357375090694,\n              40.644919434207\n            ],\n            [\n              -73.77637823323138,\n              40.626377771367885\n            ],\n            [\n              -73.81832219179216,\n              40.65233465747326\n            ],\n            [\n              -73.85334336107574,\n              40.6541883345451\n            ],\n            [\n              -73.88632841586649,\n              40.64275650554836\n            ],\n            [\n              -73.89813787992736,\n              40.61710500899537\n            ],\n            [\n              -73.88592119296749,\n              40.58433093987168\n            ],\n            [\n              -73.89895232572465,\n              40.590515956374276\n            ],\n            [\n              -73.9315301576164,\n              40.59731881385059\n            ],\n            [\n              -73.9547418628391,\n              40.58927899883426\n            ],\n            [\n              -73.9351951637045,\n              40.55401609118147\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"43","issue":"5","noUsgsAuthors":false,"publicationDate":"2023-05-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Wang, Hongqing 0000-0002-2977-7732","orcid":"https://orcid.org/0000-0002-2977-7732","contributorId":219641,"corporation":false,"usgs":true,"family":"Wang","given":"Hongqing","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":877277,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Snedden, Gregg 0000-0001-7821-3709","orcid":"https://orcid.org/0000-0001-7821-3709","contributorId":213411,"corporation":false,"usgs":true,"family":"Snedden","given":"Gregg","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":877278,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hartig, Ellen K.","contributorId":179351,"corporation":false,"usgs":false,"family":"Hartig","given":"Ellen K.","affiliations":[],"preferred":false,"id":877279,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Chen, Q. 0000-0002-6540-8758","orcid":"https://orcid.org/0000-0002-6540-8758","contributorId":56532,"corporation":false,"usgs":false,"family":"Chen","given":"Q.","affiliations":[{"id":38331,"text":"Northeastern University","active":true,"usgs":false}],"preferred":true,"id":877280,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70260123,"text":"70260123 - 2023 - Breaking plates: Creation of the East Anatolian fault, the Anatolian plate, and a tectonic escape system","interactions":[],"lastModifiedDate":"2024-10-29T13:58:16.517135","indexId":"70260123","displayToPublicDate":"2023-05-16T08:45:28","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1796,"text":"Geology","active":true,"publicationSubtype":{"id":10}},"title":"Breaking plates: Creation of the East Anatolian fault, the Anatolian plate, and a tectonic escape system","docAbstract":"<p><span>Lateral movement of lithospheric fragments along strike-slip faults in response to collision (escape tectonics) has characterized convergent settings since the onset of plate tectonics and is a mechanism for the formation of new plates. The Anatolian plate was created by the sequential connection of strike-slip faults following ≥10 m.y. of distributed deformation that ultimately localized into plate-bounding faults. Thermochronology data and seismic images of lithosphere structure near the East Anatolian fault zone (EAFZ) provide insights into the development of the new plate and escape system. Low-temperature thermochronology ages of rocks in and near the EAFZ are significantly younger than in other fault zones in the region, e.g., apatite (U-Th)/He: 11–1 Ma versus 27–13 Ma. Young apatite (U-Th)/He ages and thermal history modeling record thermal resetting along the EAFZ over the past ~5 m.y. and are interpreted to indicate thermal activity triggered by strike-slip faulting in the EAFZ as it formed as a through-going, lithosphere-scale structure. The mechanism for EAFZ formation may be discerned from S-wave velocity images from the Continental Dynamics–Central Anatolian Tectonics (CD-CAT) seismic experiment. These images indicate that thin but strong Arabian lithospheric mantle extends ~50–150 km north beneath Anatolian crust and would have been located near the present surficial location of the Bitlis-Zagros suture zone (co-located with the EAFZ in our study area) at ca. 5 Ma. Underthrusting of strong Arabian lithosphere facilitated localization of the EAFZ and thus was a fundamental control on the formation of the Anatolian plate and escape system.</span></p>","language":"English","publisher":"Geological Society of America","doi":"10.1130/G51211.1","usgsCitation":"Whitney, D., Delph, J., Thomson, S.N., Beck, S.L., Brocard, G., Cosca, M., Darin, M.H., Kaymakci, N., Meijers, M.J., Okay, A., Rojay, B., Teyssier, C., and Umhoefer, P.J., 2023, Breaking plates: Creation of the East Anatolian fault, the Anatolian plate, and a tectonic escape system: Geology, v. 51, no. 7, p. 673-677, https://doi.org/10.1130/G51211.1.","productDescription":"5 p.","startPage":"673","endPage":"677","ipdsId":"IP-146320","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":467111,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/g51211.1","text":"Publisher Index Page"},{"id":463320,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Turkey","otherGeospatial":"East Anatolian Fault","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              26.67934760909378,\n              41.23446509975915\n            ],\n            [\n              26.67934760909378,\n              36.91404497354138\n            ],\n            [\n              41.73454686971263,\n              36.91404497354138\n            ],\n            [\n              41.73454686971263,\n              41.23446509975915\n            ],\n            [\n              26.67934760909378,\n              41.23446509975915\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  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Arizona","active":true,"usgs":false}],"preferred":false,"id":917091,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Beck, Susan L.","contributorId":206719,"corporation":false,"usgs":false,"family":"Beck","given":"Susan","email":"","middleInitial":"L.","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":917083,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Brocard, Gilles","contributorId":194115,"corporation":false,"usgs":false,"family":"Brocard","given":"Gilles","affiliations":[],"preferred":false,"id":917084,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cosca, M. 0000-0002-0600-7663","orcid":"https://orcid.org/0000-0002-0600-7663","contributorId":107417,"corporation":false,"usgs":true,"family":"Cosca","given":"M.","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science 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Frankfurt","active":true,"usgs":false}],"preferred":false,"id":917088,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Okay, Aral","contributorId":345609,"corporation":false,"usgs":false,"family":"Okay","given":"Aral","email":"","affiliations":[{"id":82655,"text":"Istanbul Technical University","active":true,"usgs":false}],"preferred":false,"id":917089,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Rojay, Bora","contributorId":248206,"corporation":false,"usgs":false,"family":"Rojay","given":"Bora","email":"","affiliations":[{"id":49823,"text":"Middle East Technical University","active":true,"usgs":false}],"preferred":false,"id":917090,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Teyssier, Christian","contributorId":193450,"corporation":false,"usgs":false,"family":"Teyssier","given":"Christian","email":"","affiliations":[],"preferred":false,"id":917082,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Umhoefer, Paul J.","contributorId":200335,"corporation":false,"usgs":false,"family":"Umhoefer","given":"Paul","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":917092,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}}
,{"id":70243632,"text":"70243632 - 2023 - Rapid modeling of compound flooding across broad coastal regions and the necessity to include rainfall driven processes: A case study of Hurricane Florence (2018)","interactions":[],"lastModifiedDate":"2023-05-16T13:39:15.608596","indexId":"70243632","displayToPublicDate":"2023-05-16T08:37:56","publicationYear":"2023","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Rapid modeling of compound flooding across broad coastal regions and the necessity to include rainfall driven processes: A case study of Hurricane Florence (2018)","docAbstract":"In this work, we show that large-scale compound flood models developed for North and South Carolina, USA, can skillfully simulate multiple drivers of coastal flooding as confirmed by measurements collected during Hurricane Florence (2018). Besides the accuracy of representing observed water levels, the importance of individual processes was investigated. We demonstrate that across the area of interest, it is necessary to include marine, pluvial, and fluvial forcing and the processes of wind stress and infiltration to correctly model water levels along the coast and further inland. This work highlights the need to include these processes in modeling coastal compound flooding.  By using high-resolution topo-bathymetry that is incorporated via subgrid derived tables in the Super-Fast INundation of CoastS (SFINCS) model, we improved the skill of the model at efficiently simulating flooding across large-scale domains with locally relevant results.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Coastal Sediments 2023: Proceedings of the Coastal Sediments 2023","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"Coastal Sediments 2023","conferenceDate":"April 11-15, 2023","conferenceLocation":"New Orleans, Louisiana, United States","language":"English","publisher":"World Scientific","doi":"10.1142/9789811275135_0235","usgsCitation":"Leijnse, T., Nederhoff, C.M., Thomas, J.A., Parker, K.A., van Ormondt, M., Erikson, L.H., McCall, R.T., van Dongeren, A., O'Neill, A., and Barnard, P.L., 2023, Rapid modeling of compound flooding across broad coastal regions and the necessity to include rainfall driven processes: A case study 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,{"id":70246260,"text":"70246260 - 2023 - Rift basins and intraplate earthquakes: New high-resolution aeromagnetic data provide insights into buried structures of the Charleston, South Carolina seismic zone","interactions":[],"lastModifiedDate":"2023-06-28T13:26:15.350566","indexId":"70246260","displayToPublicDate":"2023-05-16T08:19:10","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1757,"text":"Geochemistry, Geophysics, Geosystems","active":true,"publicationSubtype":{"id":10}},"title":"Rift basins and intraplate earthquakes: New high-resolution aeromagnetic data provide insights into buried structures of the Charleston, South Carolina seismic zone","docAbstract":"<p><span>The delineation of faults that pose seismic risk in intraplate seismic zones and the mapping of features associated with failed rift basins can help our understanding of links between the two. We use new high-resolution aeromagnetic data, previous borehole sample information, and reprocessed seismic reflection profiles to image subsurface structures and evaluate recent fault activity within the Charleston seismic zone, the associated Mesozoic South Georgia rift basin, and surrounds. The new aeromagnetic data provide an unprecedented view of buried basement structures. NE- and NW-trending lineaments of various lengths throughout the survey area are interpreted as Paleozoic orogenic structures and Mesozoic dikes, respectively. Within the rift basin, 15- to 20-km long ESE-trending lineaments are associated with faults in pre-Cretaceous strata of the reflection data and are interpreted as Mesozoic rift structures. Various intersections and terminations of interpreted faults suggest rift-related reactivation of Paleozoic faults and corresponding inheritance for Mesozoic structures. The reflection data show that several Paleozoic and Mesozoic faults are associated with deformation in Cretaceous and younger sediments, suggesting reactivation in the more recent passive margin setting. Two of these faults, one NE-striking and one ESE-striking, are coincident with surficial landforms, suggesting Quaternary slip; the ESE-striking fault is also well-aligned with a plan-view offset in modern seismicity. A favorable orientation for reverse motion on ESE-striking Mesozoic faults, a possible sub-basin, and potentially weakened lithosphere are failed rift basin features that may influence intraplate seismicity within the Charleston seismic zone.</span></p>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2022GC010803","usgsCitation":"Shah, A.K., Pratt, T.L., and Horton,, J., 2023, Rift basins and intraplate earthquakes: New high-resolution aeromagnetic data provide insights into buried structures of the Charleston, South Carolina seismic zone: Geochemistry, Geophysics, Geosystems, v. 24, e2022GC010803, 25 p., https://doi.org/10.1029/2022GC010803.","productDescription":"e2022GC010803, 25 p.","ipdsId":"IP-144502","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":443523,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2022gc010803","text":"Publisher Index Page"},{"id":418582,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"South Carolina","otherGeospatial":"Charleston seismic zone","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -81.62681453773914,\n              34.845813308656375\n            ],\n            [\n              -81.62681453773914,\n              32.343066119325954\n            ],\n            [\n              -79.1425481149703,\n              32.343066119325954\n            ],\n            [\n              -79.1425481149703,\n              34.845813308656375\n            ],\n            [\n              -81.62681453773914,\n              34.845813308656375\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"24","noUsgsAuthors":false,"publicationDate":"2023-05-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Shah, Anjana K. 0000-0002-3198-081X ashah@usgs.gov","orcid":"https://orcid.org/0000-0002-3198-081X","contributorId":2297,"corporation":false,"usgs":true,"family":"Shah","given":"Anjana","email":"ashah@usgs.gov","middleInitial":"K.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":876471,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pratt, Thomas L. 0000-0003-3131-3141 tpratt@usgs.gov","orcid":"https://orcid.org/0000-0003-3131-3141","contributorId":3279,"corporation":false,"usgs":true,"family":"Pratt","given":"Thomas","email":"tpratt@usgs.gov","middleInitial":"L.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":876472,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Horton,, J. Wright Jr. 0000-0001-6756-6365","orcid":"https://orcid.org/0000-0001-6756-6365","contributorId":219824,"corporation":false,"usgs":true,"family":"Horton,","given":"J. Wright","suffix":"Jr.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":876473,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70243642,"text":"70243642 - 2023 - Incorporating wave climate complexity into modeling lower shoreface morphology and transport","interactions":[],"lastModifiedDate":"2023-05-16T12:58:28.507126","indexId":"70243642","displayToPublicDate":"2023-05-16T07:36:43","publicationYear":"2023","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Incorporating wave climate complexity into modeling lower shoreface morphology and transport","docAbstract":"<p><span>The lower shoreface, a transitional subaqueous region extending from the seaward limit of the surf zone to beyond the closure depth, serves as a sediment reservoir and pathway in sandy beach environments over annual to millennial time scales. Despite the important role this region plays in shoreline dynamics, the morphodynamics of the lower shoreface remain poorly quantified and understood. To better understand controls on shoreface morphology, here we combine energetics-based suspended sediment transport formulae (Ortiz &amp; Aston 2016) with empirical wave climate data to incorporate temporal complexity in modeled equilibrium profiles and sediment flux rates. The equilibrium shoreface shape computed using a full wave climate is steeper in shallower water and less steep in the deeper reaches compared to profiles computed using single wave characteristics. Using a full wave climate to simulate steady-state morphology will yield steeper profiles in shallow water. Suspended sediment transport rates also vary in direction and magnitude at different equilibrium profile depths and can potentially inform the location of morphodynamic boundaries in the shoreface. Our results reveal how infrequent storm waves affect shoreface slopes, with large events tending to drive sediment onshore in the deeper portions of the profile. This work explores a few ways to add complexity to simple energetics-based frameworks to reproduce empirical bathymetric data more accurately and provides insight toward refining coastal source-to-sink models.</span></p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Coastal Sediments 2023, proceedings of the 10th international conference","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"Coastal Sediments 2023","conferenceDate":"April 11-15, 2023","conferenceLocation":"New Orleans, Louisiana, United States","language":"English","publisher":"World Scientific","doi":"10.1142/9789811275135_0260","usgsCitation":"Gillen, M., Ashton, A.D., Miselis, J.L., Ciarletta, D.J., Wei, E.A., and Sherwood, C.R., 2023, Incorporating wave climate complexity into modeling lower shoreface morphology and transport, <i>in</i> Coastal Sediments 2023, proceedings of the 10th international conference, New Orleans, Louisiana, United States, April 11-15, 2023, p. 2862-2874, https://doi.org/10.1142/9789811275135_0260.","productDescription":"13 p.","startPage":"2862","endPage":"2874","ipdsId":"IP-147824","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":417085,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2023-03-23","publicationStatus":"PW","contributors":{"editors":[{"text":"Wang, Ping","contributorId":78646,"corporation":false,"usgs":false,"family":"Wang","given":"Ping","email":"","affiliations":[{"id":7163,"text":"University of South Florida","active":true,"usgs":false}],"preferred":false,"id":872817,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Royer, Elizabeth","contributorId":305463,"corporation":false,"usgs":false,"family":"Royer","given":"Elizabeth","email":"","affiliations":[],"preferred":false,"id":872818,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Rosati, Julie D.","contributorId":112486,"corporation":false,"usgs":false,"family":"Rosati","given":"Julie D.","affiliations":[{"id":7163,"text":"University of South Florida","active":true,"usgs":false}],"preferred":false,"id":872819,"contributorType":{"id":2,"text":"Editors"},"rank":3}],"authors":[{"text":"Gillen, Megan 0000-0002-2375-6519","orcid":"https://orcid.org/0000-0002-2375-6519","contributorId":267190,"corporation":false,"usgs":false,"family":"Gillen","given":"Megan","email":"","affiliations":[{"id":55436,"text":"MIT-WHOI Joint Program in Oceanography/Applied Ocean Science & Engineering, Cambridge and Woods Hole, MA, USA","active":true,"usgs":false}],"preferred":false,"id":872692,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ashton, Andrew D.","contributorId":300047,"corporation":false,"usgs":false,"family":"Ashton","given":"Andrew","email":"","middleInitial":"D.","affiliations":[{"id":16633,"text":"WHOI","active":true,"usgs":false}],"preferred":false,"id":872693,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Miselis, Jennifer L. 0000-0002-4925-3979 jmiselis@usgs.gov","orcid":"https://orcid.org/0000-0002-4925-3979","contributorId":3914,"corporation":false,"usgs":true,"family":"Miselis","given":"Jennifer","email":"jmiselis@usgs.gov","middleInitial":"L.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":872694,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ciarletta, Daniel J. 0000-0002-8555-2239","orcid":"https://orcid.org/0000-0002-8555-2239","contributorId":256700,"corporation":false,"usgs":true,"family":"Ciarletta","given":"Daniel","email":"","middleInitial":"J.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":872695,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wei, Emily A. 0000-0003-4008-0933","orcid":"https://orcid.org/0000-0003-4008-0933","contributorId":223488,"corporation":false,"usgs":true,"family":"Wei","given":"Emily","email":"","middleInitial":"A.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":872696,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sherwood, Christopher R. 0000-0001-6135-3553 csherwood@usgs.gov","orcid":"https://orcid.org/0000-0001-6135-3553","contributorId":2866,"corporation":false,"usgs":true,"family":"Sherwood","given":"Christopher","email":"csherwood@usgs.gov","middleInitial":"R.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":872697,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70244217,"text":"70244217 - 2023 - Guidance for parameterizing post-fire hydrologic models with in situ infiltration measurements","interactions":[],"lastModifiedDate":"2024-06-18T13:52:44.245324","indexId":"70244217","displayToPublicDate":"2023-05-16T07:20:50","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1425,"text":"Earth Surface Processes and Landforms","active":true,"publicationSubtype":{"id":10}},"title":"Guidance for parameterizing post-fire hydrologic models with in situ infiltration measurements","docAbstract":"<div class=\"abstract-group  metis-abstract\"><div class=\"article-section__content en main\"><p>Wildfire can alter soil-hydraulic properties, often resulting in an increased prevalence of infiltration-excess overland flow and greater potential for debris-flow hazards. Mini disk tension infiltrometers (MDIs) can be used to estimate soil hydraulic properties, such as field-saturated hydraulic conductivity (<i>K</i><sub><i>fs</i></sub>) and wetting front potential (<i>H</i><sub><i>f</i></sub>), and their spatial variability following wildfire. However, the small (point-scale) footprint of MDI measurements makes it challenging to use these data to parameterize hydrologic models at the hillslope and watershed scales where hydrologic hazards, such as debris flows, initiate. Here, we designed numerical experiments to estimate spatially constant or watershed-scale effective hydrologic parameters (EHPs) that approximate the response of spatially variable hydrologic parameters with distributions derived from MDI measurements at five sites in the southwestern United States. We found that it is possible to define EHPs for both<span>&nbsp;</span><i>K</i><sub><i>fs</i></sub><span>&nbsp;</span>and<span>&nbsp;</span><i>H</i><sub><i>f</i></sub><span>&nbsp;</span>based on the MDI measurements that lead to reasonable approximations of run-off hydrographs at the outlets of small watersheds (&lt;1&nbsp;km<sup>2</sup>). We found that watershed EHPs are functions of rainfall characteristics, although they are most sensitive to rainfall intensity and relatively less sensitive to the temporal distribution of rainfall. EHPs are lower than the arithmetic mean of the MDI measurements and are better approximated by the median or geometric mean of the MDI measurements, particularly for storms with recurrence intervals of approximately 1&nbsp;year or less that commonly initiate post-fire debris flows. This work demonstrated that using the proposed upscaling method to estimate watershed-scale EHPs, as opposed to approximating EHPs based on the arithmetic mean of the MDI measurements, improved the ability of a hydrologic model to identify storms that are likely to produce debris flows. Results improved our ability to link point-scale MDI measurements and watershed-scale EHPs in post-fire settings and helped guide our ability to use MDI data to parameterize post-fire hydrologic models.</p></div></div>","language":"English","publisher":"Wiley","doi":"10.1002/esp.5633","usgsCitation":"Liu, T., McGuire, L.A., Youberg, A., Gorr, A.N., and Rengers, F.K., 2023, Guidance for parameterizing post-fire hydrologic models with in situ infiltration measurements: Earth Surface Processes and Landforms, v. 48, no. 12, p. 2368-2386, https://doi.org/10.1002/esp.5633.","productDescription":"19 p.","startPage":"2368","endPage":"2386","ipdsId":"IP-148977","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":467112,"rank":2,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://repository.library.noaa.gov/view/noaa/63519","text":"External Repository"},{"id":417906,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.er.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, New Mexico","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -112.26119528509261,\n              35.55675438864914\n            ],\n            [\n              -112.26119528509261,\n              31.15593597909364\n            ],\n            [\n              -106.28719594621933,\n              31.15593597909364\n            ],\n            [\n              -106.28719594621933,\n              35.55675438864914\n            ],\n            [\n              -112.26119528509261,\n              35.55675438864914\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"48","issue":"12","noUsgsAuthors":false,"publicationDate":"2023-05-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Liu, T. 0000-0002-7394-9415","orcid":"https://orcid.org/0000-0002-7394-9415","contributorId":306158,"corporation":false,"usgs":false,"family":"Liu","given":"T.","email":"","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":874897,"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":874898,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Youberg, Ann 0000-0002-2005-3674","orcid":"https://orcid.org/0000-0002-2005-3674","contributorId":105919,"corporation":false,"usgs":false,"family":"Youberg","given":"Ann","affiliations":[],"preferred":false,"id":874899,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gorr, Alexander N.","contributorId":306159,"corporation":false,"usgs":false,"family":"Gorr","given":"Alexander","email":"","middleInitial":"N.","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":874900,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"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":874901,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70243648,"text":"70243648 - 2023 - Assessing environmental oil spill based on fluorescence images of water samples and deep learning","interactions":[],"lastModifiedDate":"2023-11-15T14:28:58.902573","indexId":"70243648","displayToPublicDate":"2023-05-16T07:17:34","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5261,"text":"Journal of Environmental Informatics","onlineIssn":"16848799","printIssn":"17262135","active":true,"publicationSubtype":{"id":10}},"title":"Assessing environmental oil spill based on fluorescence images of water samples and deep learning","docAbstract":"Measuring oil concentration in the aquatic environment is essential for determining the potential exposure, risk, or injury for oil spill response and natural resource damage assessment. Conventional analytical chemistry methods require samples to be collected in the field, shipped, and processed in the laboratory, which is also rather time-consuming, laborious, and costly. For rapid field response immediately after a spill, there is a need to estimate oil concentration in near real time. To make the oil analysis more portable, fast, and cost effective, we developed a plug-and-play device and a deep learning model to assess oil levels in water using fluorescent images of water samples. We constructed a 3D-printed device to collect fluorescent images of solvent-extracted water samples using an iPhone. We prepared approximately 1,300 samples of oil at different concentrations to train and test the deep learning model. The model comprises a convolutional neural network and a novel module of histogram bottleneck block with an attention mechanism to exploit the spectral features found in low-contrast images. This model predicts the oil concentration in weight per volume based on fluorescence image. We devised a confidence interval estimator by combining gradient boosting and polymodal regressor to provide a confidence assessment of our results. Our model achieved sufficient accuracy to predict oil levels for most environmental applications. We plan to improve the device and iPhone application as a near-real-time tool for oil spill responders to measure oil in water.","language":"English","publisher":"International Society for Environmental Information Sciences","doi":"10.3808/jei.202300491","usgsCitation":"Liu, D.P., Liu, M., Sun, G., Zhou, Z., Wang, D., He, F., Li, J., Xie, J., Gettler, R., Brunson, E., Steevens, J.A., and Xu, D., 2023, Assessing environmental oil spill based on fluorescence images of water samples and deep learning: Journal of Environmental Informatics, v. 42, no. 1, p. 1-12, https://doi.org/10.3808/jei.202300491.","productDescription":"12 p.","startPage":"1","endPage":"12","ipdsId":"IP-130838","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":443532,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3808/jei.202300491","text":"Publisher Index Page"},{"id":417084,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"42","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Liu, D. P.","contributorId":305462,"corporation":false,"usgs":false,"family":"Liu","given":"D.","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":872816,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Liu, Ming","contributorId":305408,"corporation":false,"usgs":false,"family":"Liu","given":"Ming","email":"","affiliations":[{"id":6754,"text":"University of Missouri","active":true,"usgs":false}],"preferred":false,"id":872712,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sun, Guangyu","contributorId":305409,"corporation":false,"usgs":false,"family":"Sun","given":"Guangyu","email":"","affiliations":[{"id":6754,"text":"University of Missouri","active":true,"usgs":false}],"preferred":false,"id":872713,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zhou, Zhiqian","contributorId":305410,"corporation":false,"usgs":false,"family":"Zhou","given":"Zhiqian","email":"","affiliations":[{"id":6754,"text":"University of Missouri","active":true,"usgs":false}],"preferred":false,"id":872714,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wang, Duolin","contributorId":305411,"corporation":false,"usgs":false,"family":"Wang","given":"Duolin","email":"","affiliations":[{"id":6754,"text":"University of Missouri","active":true,"usgs":false}],"preferred":false,"id":872715,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"He, Fei","contributorId":305412,"corporation":false,"usgs":false,"family":"He","given":"Fei","email":"","affiliations":[{"id":6754,"text":"University of Missouri","active":true,"usgs":false}],"preferred":false,"id":872716,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Li, Jiaxin","contributorId":305413,"corporation":false,"usgs":false,"family":"Li","given":"Jiaxin","email":"","affiliations":[{"id":6754,"text":"University of Missouri","active":true,"usgs":false}],"preferred":false,"id":872717,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Xie, Jiacheng","contributorId":331598,"corporation":false,"usgs":false,"family":"Xie","given":"Jiacheng","email":"","affiliations":[],"preferred":false,"id":888166,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Gettler, Ryan","contributorId":305415,"corporation":false,"usgs":false,"family":"Gettler","given":"Ryan","email":"","affiliations":[{"id":6754,"text":"University of Missouri","active":true,"usgs":false}],"preferred":false,"id":872718,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Brunson, Eric 0000-0001-6624-0902","orcid":"https://orcid.org/0000-0001-6624-0902","contributorId":201761,"corporation":false,"usgs":true,"family":"Brunson","given":"Eric","email":"","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":872719,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Steevens, Jeffery A. 0000-0003-3946-1229","orcid":"https://orcid.org/0000-0003-3946-1229","contributorId":207511,"corporation":false,"usgs":true,"family":"Steevens","given":"Jeffery","middleInitial":"A.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":872720,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Xu, Dong","contributorId":305418,"corporation":false,"usgs":false,"family":"Xu","given":"Dong","email":"","affiliations":[{"id":6754,"text":"University of Missouri","active":true,"usgs":false}],"preferred":false,"id":872721,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}}
,{"id":70243633,"text":"70243633 - 2023 - New capabilities in MT3D-USGS for simulating unsaturated-zone heat transport","interactions":[],"lastModifiedDate":"2023-05-16T12:13:26.00482","indexId":"70243633","displayToPublicDate":"2023-05-16T07:10:26","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3825,"text":"Groundwater","active":true,"publicationSubtype":{"id":10}},"title":"New capabilities in MT3D-USGS for simulating unsaturated-zone heat transport","docAbstract":"Changes in climate and land use will alter groundwater heat transport dynamics in the future.  These changes will in turn affect watershed processes (e.g., nutrient cycling) as well as watershed characteristics (e.g., distribution and persistence of cold-water habitat). Thus, groundwater flow and heat transport models at watershed scales that can characterize and quantify thermal impacts of surface temperature change on groundwater system temperatures are needed to forecast changes to groundwater-linked ecosystems in riparian zones, streams, and lakes.  Including unsaturated zone processes has previously been shown to be important for properly determining the timing and magnitude of groundwater recharge (Hunt et al. 2008).  Similarly, heat transport dynamics in the saturated-zone, as well as connected surface-water systems, can be appreciably influenced by unsaturated-zone processes; in this way the unsaturated zone forms an inextricable link between land surface where change occurs and the groundwater system that transmit that change.  This paper presents new capabilities for the existing MT3D-USGS transport simulator by adding functionality for simulating heat transport through the unsaturated zone.  New simulation capabilities are verified through comparison of simulation results with those of the variably-saturated heat transport simulator VS2DH under steady and transient conditions for both water and heat flow.  The new capabilities are assessed using a number of conceptualizations and include evaluations of convective and conductive heat flow.  These additional capabilities increase the utility for applied watershed-scale simulations, which in turn should facilitate more realistic characterizations of temperature change on thermally sensitive ecosystems, such as stream habitat.","language":"English","publisher":"Wiley","doi":"10.1111/gwat.13256","usgsCitation":"Morway, E.D., Feinstein, D., Hunt, R., and Healy, R.W., 2023, New capabilities in MT3D-USGS for simulating unsaturated-zone heat transport: Groundwater, v. 61, no. 3, p. 330-345, https://doi.org/10.1111/gwat.13256.","productDescription":"16 p.","startPage":"330","endPage":"345","ipdsId":"IP-134625","costCenters":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":435334,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9PGFNY2","text":"USGS data release","linkHelpText":"MODFLOW-NWT, MT3D-USGS, and VS2DH models of 6 hypothetical 1-dimensional variably saturated systems to demonstrate the accuracy of new heat transport capabilities in MT3D-USGS"},{"id":417083,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"61","issue":"3","noUsgsAuthors":false,"publicationDate":"2022-09-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Morway, Eric D. 0000-0002-8553-6140 emorway@usgs.gov","orcid":"https://orcid.org/0000-0002-8553-6140","contributorId":4320,"corporation":false,"usgs":true,"family":"Morway","given":"Eric","email":"emorway@usgs.gov","middleInitial":"D.","affiliations":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"preferred":true,"id":872680,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Feinstein, Daniel T. 0000-0003-1151-2530","orcid":"https://orcid.org/0000-0003-1151-2530","contributorId":203888,"corporation":false,"usgs":true,"family":"Feinstein","given":"Daniel T.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":872681,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hunt, Randall J. 0000-0001-6465-9304","orcid":"https://orcid.org/0000-0001-6465-9304","contributorId":208800,"corporation":false,"usgs":true,"family":"Hunt","given":"Randall J.","affiliations":[],"preferred":true,"id":872682,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Healy, Richard W. 0000-0002-0224-1858 rwhealy@usgs.gov","orcid":"https://orcid.org/0000-0002-0224-1858","contributorId":658,"corporation":false,"usgs":true,"family":"Healy","given":"Richard","email":"rwhealy@usgs.gov","middleInitial":"W.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":872683,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70257250,"text":"70257250 - 2023 - A multi-level modeling approach to guide management of female feral hogs in Great Smoky Mountains National Park","interactions":[],"lastModifiedDate":"2024-08-14T12:02:24.968018","indexId":"70257250","displayToPublicDate":"2023-05-16T06:56:01","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1018,"text":"Biological Invasions","active":true,"publicationSubtype":{"id":10}},"title":"A multi-level modeling approach to guide management of female feral hogs in Great Smoky Mountains National Park","docAbstract":"<div id=\"Abs1-section\" class=\"c-article-section\"><div id=\"Abs1-content\" class=\"c-article-section__content\"><p>We trapped, anesthetized, and fit 16 female feral swine (<i>Sus scrofa</i>) with Global Positioning System (GPS) collars in Great Smoky Mountains National Park (GRSM) to develop predictive summer and winter models for more effective population control efforts. Given the highly diverse habitat and topography in GRSM and the spatial extent of our dataset, we employed Step Selection Function (SSF) to evaluate resource selection at the 3<sup>rd</sup>-order level and Resource Selection Function (RSF) models at the 2<sup>nd</sup>-order level for both summer and winter seasons. The summer SSF and RSF models suggested relatively similar levels of selection, whereas the winter models differed by method. We created a straightforward consensus model to better visualize the agreement and constraints of each set of models. In summer, feral swine used lower slopes regardless of elevation, especially those closer to human-dominated spaces such as along paved and gravel roadways. In winter, feral swine maintained preference for lower slopes but preferred oak-dominated forest areas and selection for human development was less than in summer. Wildlife managers can use these models to better focus feral swine surveillance and management in GRSM. Managers can identify areas of high use by season and plan control activities that are both accessible and highly efficient. The combination and consensus framework presented here can be applied to other systems where species’ habitat selection may result in incongruous results across different levels of selection or seasons of interest.</p></div></div>","language":"English","publisher":"Springer","doi":"10.1007/s10530-023-03086-4","usgsCitation":"Buderman, F.E., Helm, P.J., Clark, J.D., Williamson, R.H., Yarkovich, J.G., and Mullinax, J.M., 2023, A multi-level modeling approach to guide management of female feral hogs in Great Smoky Mountains National Park: Biological Invasions, v. 25, p. 3065-3082, https://doi.org/10.1007/s10530-023-03086-4.","productDescription":"18 p.","startPage":"3065","endPage":"3082","ipdsId":"IP-145427","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":443537,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10530-023-03086-4","text":"Publisher Index Page"},{"id":432647,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Tennessee","otherGeospatial":"Great Smoky Mountains National Park","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -84.15529114629751,\n              36.084555007287705\n            ],\n            [\n              -84.15529114629751,\n              35.33907301330092\n            ],\n            [\n              -82.56681547720542,\n              35.33907301330092\n            ],\n            [\n              -82.56681547720542,\n              36.084555007287705\n            ],\n            [\n              -84.15529114629751,\n              36.084555007287705\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"25","noUsgsAuthors":false,"publicationDate":"2023-05-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Buderman, Frances E.","contributorId":171634,"corporation":false,"usgs":false,"family":"Buderman","given":"Frances","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":909765,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Helm, Patrick J.","contributorId":342169,"corporation":false,"usgs":false,"family":"Helm","given":"Patrick","email":"","middleInitial":"J.","affiliations":[{"id":12716,"text":"University of Tennessee","active":true,"usgs":false}],"preferred":false,"id":909766,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Clark, Joseph D. 0000-0002-8547-8112 jclark1@usgs.gov","orcid":"https://orcid.org/0000-0002-8547-8112","contributorId":2265,"corporation":false,"usgs":true,"family":"Clark","given":"Joseph","email":"jclark1@usgs.gov","middleInitial":"D.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":909767,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Williamson, Ryan H.","contributorId":342170,"corporation":false,"usgs":false,"family":"Williamson","given":"Ryan","email":"","middleInitial":"H.","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":909768,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Yarkovich, Joseph G.","contributorId":244820,"corporation":false,"usgs":false,"family":"Yarkovich","given":"Joseph","email":"","middleInitial":"G.","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":909769,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Mullinax, Jennifer M.","contributorId":221170,"corporation":false,"usgs":false,"family":"Mullinax","given":"Jennifer","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":909770,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70243462,"text":"sir20235008 - 2023 - Assessing potential effects of changes in water use in the middle Carson River Basin with a numerical groundwater-flow model, Eagle, Dayton, and Churchill Valleys, west-central Nevada","interactions":[],"lastModifiedDate":"2023-05-16T15:56:39.238633","indexId":"sir20235008","displayToPublicDate":"2023-05-15T13:56:57","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":"2023-5008","displayTitle":"Assessing Potential Effects of Changes in Water Use in the Middle Carson River Basin with a Numerical Groundwater-Flow Model, Eagle, Dayton, and Churchill Valleys, West-Central Nevada","title":"Assessing potential effects of changes in water use in the middle Carson River Basin with a numerical groundwater-flow model, Eagle, Dayton, and Churchill Valleys, west-central Nevada","docAbstract":"<p>During the economic boom of the mid part of the first decade of the 2000s in northwestern Nevada, municipal and housing growth increased use of the water resources of this semi-arid region. In 2008, when the economy slowed, new housing development stopped, and immediate pressure on groundwater resources abated. The U.S. Geological Survey, in cooperation with the Bureau of Reclamation, began a hydrogeologic study of the middle Carson River Basin. The first half of the study reviewed and synthesized previous geologic studies and contributed new datasets that served as a foundation for a three-dimensional, transient numerical model of groundwater and surface-water flow for the middle Carson River Basin extending from Eagle Valley to Churchill Valley. The model can be used to evaluate the effects of proposed alternative management strategies on groundwater sustainability, flows in the Carson River, and routine operation of Lahontan Reservoir and can also provide a basis for basin-wide investigations seeking to quantitatively evaluate the effects of climate change or yet-to-be-determined alternative management strategies.</p><p>The middle Carson model was constructed using the U.S. Geological Survey groundwater modeling software MODFLOW-NWT. MODFLOW is widely used groundwater modeling software and is well-suited for evaluating groundwater and surface-water interactions. The model uses 550-feet square grid cells that align with the previously published model for Carson Valley (adjacent upstream valley). Six grid layers with more finely resolved vertical resolution near the perimeter of the active model domain and near surface-water features, compared to other areas of the active model domain, hone the simulated groundwater and surface-water exchanges. In addition to simulating groundwater and surface-water interaction, crop and phreatophyte evapotranspiration, lake evaporation, mountain-front recharge, recharge from irrigation return flows, and groundwater pumping are also simulated. Surface-water flow entering the model domain, including the Carson River, tributary inflow from perennial streams in Eagle Valley, and trans-basin imports through the Truckee Canal (surface water diverted from the Truckee River) are specified according to U.S. Geological Survey streamgage records. Groundwater pumpage and surface-water diversions to 10 agricultural ditches and the managed release from Lahontan Reservoir, at the end of the middle Carson River Basin, are specified according to water-manager records.</p><p>The model simulation period extended from 2000 through 2010 (January 1, 2000, to December 31, 2010) using 574 weekly stress periods, with a single steady-state stress period at the beginning of the simulation that establishes initial conditions by approximating average conditions during the transient simulation period. All available observations for this period were used during the model calibration process, performed using automated parameter-estimation software. Calibration targets included observations of groundwater elevations in wells, streamflow, differences in observed streamflow between successive streamgages and actual evapotranspiration from irrigated lands. Among all 5,296 simulated and observed groundwater level pairs, the mean error was 1.42 feet; the mean absolute error, 7.71 feet; and the percent bias was −0.1 percent.</p><p>Three alternative management scenarios, run using the entire period of analysis (2000–10), were simulated to improve understanding of the potential effects of (1) loss of irrigated agricultural lands following conversion of water-rights to municipal groundwater rights; (2) reclaiming treated wastewater with induction wells; and (3) exercising permitted but under-utilized groundwater rights. Scenarios 2 and 3 were further explored using two and four subscenarios, respectively. Simulated scenario results ranged from having little effect on the groundwater system relative to a baseline simulation to having spatially extensive and large groundwater-level declines (10 to 20 feet) compared to the baseline simulation. None of the simulated scenarios increased delivery of river flows to Lahontan Reservoir. On the contrary, one of the subscenarios under alternative management scenario 3 led to surface-water delivery shortfalls of more than 10,000 acre-feet per year.</p><p>Future model improvements may include an extension of the model simulation period backward and forward in time and directly linking it to the upstream Carson Valley groundwater model. Furthermore, converting this MODFLOW model to a GSFLOW model, which fully integrates groundwater and surface-water flows including precipitation runoff and infiltration, may provide an improved tool for comprehensive management of water-resources in the middle Carson River Basin.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235008","collaboration":"Prepared in cooperation withv the Bureau of Reclamation","usgsCitation":"Morway, E.D., Buto, S.G., Niswonger, R.G., and Huntington, J.L., 2023, Assessing potential effects of changes in water use in the middle Carson River Basin with a numerical groundwater-flow model, Eagle, Dayton, and Churchill Valleys, west-central Nevada: U.S. Geological Survey Scientific Investigations Report 2023–5008, 112 p., https://doi.org/​10.3133/​sir20235008.","productDescription":"Report: xiii, 112 p.; 3 Data Releases","numberOfPages":"112","onlineOnly":"Y","ipdsId":"IP-034336","costCenters":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"links":[{"id":416912,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9D3XO1U","text":"Data for the report assessing potential effects of changes in water use in the middle Carson River Basin with a numerical groundwater-flow model, Eagle, Dayton, and Churchill Valleys, west-central Nevada","description":"Morway, E.D., Buto, S.G., and Medina, R.L., 2023, Data for the report assessing potential effects of changes in water use in the middle Carson River Basin with a numerical groundwater-flow model, Eagle, Dayton, and Churchill Valleys, west-central Nevada: U.S. Geological Survey data release, https://doi.org/​10.5066/​P9D3XO1U."},{"id":416913,"rank":8,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9N9FNQZ","text":"MODFLOW-NWT model used to simulate potential effects of changes in water use in the middle Carson River Basin, Eagle, Dayton, and Churchill Valleys, west-central, Nevada","description":"Morway, E.D., Niswonger, R.G., and Buto, S.G., 2023, MODFLOW-NWT model used to simulate potential effects of changes in water use in the middle Carson River Basin, Eagle, Dayton, and Churchill Valleys, west-central, Nevada: U.S. Geological Survey data release, https://doi.org/​10.5066/​P9N9FNQZ."},{"id":416907,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5008/covrthb.jpg"},{"id":416908,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5008/sir20235008.pdf","text":"Report","size":"18 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":416909,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5008/sir20235008.xml"},{"id":416910,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5008/images"},{"id":416911,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20235008/full"},{"id":416921,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9P5LJ3P","text":"Data for the report Geologic Framework and Hydrogeology of the middle Carson River basin, Eagle, Dayton, and Churchill Valleys, West-Central Nevada","description":"Maurer, D.K., and Medina, R.L., 2020, Data for the report Geologic Framework and Hydrogeology of the middle Carson River basin, Eagle, Dayton, and Churchill Valleys, West-Central Nevada: U.S. Geological Survey data release, https://doi.org/​10.5066/​P9P5LJ3P."}],"country":"United States","state":"Nevada","otherGeospatial":"Middle Carson River Basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -120,\n              40.5\n            ],\n            [\n              -120,\n              38\n            ],\n            [\n              -118,\n              38\n            ],\n            [\n              -118,\n              40.5\n            ],\n            [\n              -120,\n              40.5\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","contact":"<p><a href=\"mailto:dc_nv@usgs.gov\" data-mce-href=\"mailto:dc_nv@usgs.gov\">Director</a>,<br><a href=\"https://www.usgs.gov/centers/nv-water\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov/centers/nv-water\">Nevada Water Science Center</a><br><a href=\"https://usgs.gov/\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://usgs.gov\">U.S. Geological Survey</a><br>2730 N. Deer Run Road<br>Carson City, Nevada 89701</p>","tableOfContents":"<ul><li>Acknowledgements</li><li>Abstract</li><li>Introduction</li><li>Previous Investigations</li><li>Modeling Approach</li><li>Construction of the Groundwater Flow Model</li><li>Model Calibration</li><li>Assessment of Baseline Model Calibration</li><li>Simulated Canal Seepage</li><li>Assessment of Alternative Management Strategies</li><li>Model Limitations and Suggestions for Future Work</li><li>Summary</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"publishedDate":"2023-05-15","noUsgsAuthors":false,"publicationDate":"2023-05-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Morway, Eric D. 0000-0002-8553-6140 emorway@usgs.gov","orcid":"https://orcid.org/0000-0002-8553-6140","contributorId":4320,"corporation":false,"usgs":true,"family":"Morway","given":"Eric","email":"emorway@usgs.gov","middleInitial":"D.","affiliations":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"preferred":true,"id":872212,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Buto, Susan G. 0000-0002-1107-9549 sbuto@usgs.gov","orcid":"https://orcid.org/0000-0002-1107-9549","contributorId":1057,"corporation":false,"usgs":true,"family":"Buto","given":"Susan","email":"sbuto@usgs.gov","middleInitial":"G.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true},{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"preferred":true,"id":872213,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Niswonger, Richard G. 0000-0001-6397-2403 rniswon@usgs.gov","orcid":"https://orcid.org/0000-0001-6397-2403","contributorId":197892,"corporation":false,"usgs":true,"family":"Niswonger","given":"Richard","email":"rniswon@usgs.gov","middleInitial":"G.","affiliations":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":872214,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Huntington, Justin L.","contributorId":305173,"corporation":false,"usgs":true,"family":"Huntington","given":"Justin","email":"","middleInitial":"L.","affiliations":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"preferred":true,"id":872215,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70243592,"text":"70243592 - 2023 - Flushing time variability in a short, low-inflow estuary","interactions":[],"lastModifiedDate":"2023-05-15T15:17:07.139375","indexId":"70243592","displayToPublicDate":"2023-05-15T09:56:27","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1587,"text":"Estuarine, Coastal and Shelf Science","active":true,"publicationSubtype":{"id":10}},"title":"Flushing time variability in a short, low-inflow estuary","docAbstract":"<p><span>Flushing time, the time scale for exchange and mixing between embayed and oceanic waters in an&nbsp;estuary, plays an integral role in determining water quality and&nbsp;aquatic ecosystem&nbsp;health. Here, we investigated the spatiotemporal variability of flushing times throughout Morro Bay, a short, low-inflow estuary (LIE) on the California coast, using a calibrated and validated hydrodynamic model (Delft3D). Morro Bay has historically supported an extensive&nbsp;eelgrass&nbsp;(</span><span><i>Zostera</i><i>&nbsp;marina</i></span><span>) habitat, which declined substantially from 139 to 5.4&nbsp;ha during 2007–2017. Eelgrass decline motivated the current research into the role of changing&nbsp;bed roughness&nbsp;and oceanic drivers (i.e., tide and sea-level rise) on estuarine hydrodynamics and flushing times. We found that tidal variability exerts the strongest control on flushing times compared to other effects, i.e., bed roughness or sea-level rise. Additionally, we found that increasing sea level and decreasing bed roughness (associated with declining&nbsp;seagrass&nbsp;coverage) yielded higher rates of mixing (lower flushing times). We detected a strong correspondence between areas having shorter flushing times (e.g., near the estuary mouth) and areas occupied by resilient eelgrass populations in Morro Bay. Our findings further indicated that flushing times in short LIEs are particularly sensitive to several factors (e.g., bed roughness, sea level) that are susceptible to anthropogenic disturbance and future climate change.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecss.2023.108277","usgsCitation":"Taherkhani, M., Vitousek, S., Walter, R.K., O’Leary, J., and Khodadoust, A.P., 2023, Flushing time variability in a short, low-inflow estuary: Estuarine, Coastal and Shelf Science, v. 284, 108277, 16 p., https://doi.org/10.1016/j.ecss.2023.108277.","productDescription":"108277, 16 p.","ipdsId":"IP-149301","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":443542,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecss.2023.108277","text":"Publisher Index Page"},{"id":417031,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Morro Bay","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -120.86550507818211,\n              35.37559917233456\n            ],\n            [\n              -120.8609393073724,\n              35.352727225376455\n            ],\n            [\n              -120.86354831926357,\n              35.33197729831399\n            ],\n            [\n              -120.87072310196481,\n              35.306963896126035\n            ],\n            [\n              -120.834849188459,\n              35.3218664291451\n            ],\n            [\n              -120.81267258738302,\n              35.32931666587521\n            ],\n            [\n              -120.82441314089395,\n              35.36389805553908\n            ],\n            [\n              -120.86550507818211,\n              35.37559917233456\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"284","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Taherkhani, Mohsen","contributorId":223951,"corporation":false,"usgs":false,"family":"Taherkhani","given":"Mohsen","affiliations":[{"id":18137,"text":"University of Illinois at Chicago","active":true,"usgs":false}],"preferred":false,"id":872546,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Vitousek, Sean 0000-0002-3369-4673 svitousek@usgs.gov","orcid":"https://orcid.org/0000-0002-3369-4673","contributorId":149065,"corporation":false,"usgs":true,"family":"Vitousek","given":"Sean","email":"svitousek@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":872547,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Walter, Ryan K.","contributorId":241045,"corporation":false,"usgs":false,"family":"Walter","given":"Ryan","email":"","middleInitial":"K.","affiliations":[{"id":16725,"text":"California Polytechnic State University, San Luis Obispo","active":true,"usgs":false}],"preferred":false,"id":872548,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"O’Leary, Jennifer","contributorId":305371,"corporation":false,"usgs":false,"family":"O’Leary","given":"Jennifer","email":"","affiliations":[{"id":13272,"text":"Wildlife Conservation Society","active":true,"usgs":false}],"preferred":false,"id":872549,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Khodadoust, Amid P.","contributorId":305372,"corporation":false,"usgs":false,"family":"Khodadoust","given":"Amid","email":"","middleInitial":"P.","affiliations":[{"id":18137,"text":"University of Illinois at Chicago","active":true,"usgs":false}],"preferred":false,"id":872550,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70269799,"text":"70269799 - 2023 - Assessment and characterization of ephemeral stream channel stability in the Grand Valley, Colorado, 2018-22","interactions":[],"lastModifiedDate":"2025-08-04T13:54:33.905692","indexId":"70269799","displayToPublicDate":"2023-05-15T08:44:42","publicationYear":"2023","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Assessment and characterization of ephemeral stream channel stability in the Grand Valley, Colorado, 2018-22","docAbstract":"The purpose of this study is to provide information regarding the stability of ephemeral streams on the north side of the Grand Valley, Colorado. The ungaged ephemeral streams in this semiarid region are of particular interest because (1) the underlying bedrock geology, Mancos Shale, is a sedimentary rock deposit that has been identified as a major contributor of salinity to the Colorado River and (2) despite infrequent flows of short duration, monsoon derived floods in these ephemeral streams can carry substantial amounts of sediment downstream, affecting up and downstream banks and channel cross sections. The study area is of interest as salinity, or the total dissolved solids concentration, in the Colorado River causes an estimated $300 to $400 million per year in economic damages in the United States and it is estimated that 62% of Upper Colorado River Basin dissolved-solid loads originate from geologic sources. In an effort to minimize salt contributions to the Colorado River from public lands administered by the Bureau of Land Management (BLM) a comprehensive three-pronged salinity control approach is being used which incorporates (1) controlling point sources of salinity; (2) controlling nonpoint sources of salinity; and (3) preventing nonpoint sources of salinity from persisting.\n\nIn 2018, the U.S. Geological Survey, in cooperation with BLM, began an assessment of ephemeral streams located in the north side of the Grand Valley, Colorado, to characterize stream channel stability. The USGS developed a method for automatically extracting channel cross-section geometry from existing remotely sensed terrain models. Based on estimated flood stage and surrogate streamflows, hydraulic characteristics were calculated. Furthermore, the channel geometries and hydraulic characteristics were used to estimate channel stability utilizing a statistical model. \n\nIn this ongoing study, cross-section stabilities were determined from a stream channel stability assessment for a subset of 1,406 visited locations out of a desired 13,415 cross sections which were delineated from remotely sensed terrain models. The application of Manning’s resistance equation in combination with multiple Logistic Regression models demonstrated that channel stability can be estimated with an 0.85 goodness of fit for a validation dataset when using a combination of drainage area, width to depth ratio, sinuosity, and shear stress as the explanatory variables. Stream channel stability was extrapolated for the remaining 13,415 unvisited cross sections using the multiple Logistic Regression model and defined explanatory variables. Mapping the ephemeral streams and their associated stabilities could be used to prioritize areas for BLM remediation or changes in management strategies to reduce sediment and salinity loading to the Colorado River.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of SEDHYD 2023","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"SEDHYD","usgsCitation":"Homan, J.W., 2023, Assessment and characterization of ephemeral stream channel stability in the Grand Valley, Colorado, 2018-22, <i>in</i> Proceedings of SEDHYD 2023, 11 p.","productDescription":"11 p.","ipdsId":"IP-148840","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":493408,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":493407,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.sedhyd.org/past/"}],"country":"United States","state":"Colorado","otherGeospatial":"Grand Valley","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -109.0445924965195,\n              39.26086521028847\n            ],\n            [\n              -109.0445924965195,\n              38.99358861682228\n            ],\n            [\n              -108.24066157334559,\n              38.99358861682228\n            ],\n            [\n              -108.24066157334559,\n              39.26086521028847\n            ],\n            [\n              -109.0445924965195,\n              39.26086521028847\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationDate":"2023-05-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Homan, Joel William 0000-0002-6709-123X","orcid":"https://orcid.org/0000-0002-6709-123X","contributorId":315495,"corporation":false,"usgs":true,"family":"Homan","given":"Joel","email":"","middleInitial":"William","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":944644,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70243604,"text":"70243604 - 2023 - A numerical investigation of the mechanisms controlling salt intrusion in the Delaware Bay Estuary","interactions":[],"lastModifiedDate":"2023-05-15T14:03:31.182073","indexId":"70243604","displayToPublicDate":"2023-05-15T08:43:17","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1587,"text":"Estuarine, Coastal and Shelf Science","active":true,"publicationSubtype":{"id":10}},"title":"A numerical investigation of the mechanisms controlling salt intrusion in the Delaware Bay Estuary","docAbstract":"<p><span>Salinity intrusion in coastal systems is mainly controlled by freshwater inflows. However, extreme events like drought, low-pressure storms, and longer-term&nbsp;sea level rise&nbsp;can exacerbate the landward salt migration and threaten economic infrastructure and ecological health. Along the eastern seaboard of the United States, approximately 13 million people rely on the water resources of the Delaware River basin. Salinity intrusion is actively managed through river discharge targets to suppress the propagation of the salt front (∼0.52 daily averaged psu line). The purpose of this study is to examine the mechanisms controlling the location of the salt front in the Delaware Bay&nbsp;estuary&nbsp;using a calibrated three-dimensional hydrodynamic model, the Coupled Ocean Atmosphere Wave and Sediment Transport modeling system. This study explored how river discharge, tidal motions, interactions with bathymetric and topographic features, and meteorological events affected the location of the salt front. The model was forced with tides, subtidal water levels, bulk atmospheric conditions, and waves. Compared with the observationally derived location of the salt front line, the model captured the major dynamics throughout the year and performed particularly well during times of low discharge, when salinity intruded up estuary at a constant rate of 0.4&nbsp;km</span><i>/day</i><span>. The daily average salt front moved almost 16&nbsp;km (10 mi) within a neap-spring&nbsp;tidal cycle, and low-pressure storm systems were found to move the daily averaged salt front by 13–16&nbsp;km in one event.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecss.2023.108257","usgsCitation":"Cook, S.E., Warner, J.C., and Russell, K.L., 2023, A numerical investigation of the mechanisms controlling salt intrusion in the Delaware Bay Estuary: Estuarine, Coastal and Shelf Science, v. 283, 108257, 16 p., https://doi.org/10.1016/j.ecss.2023.108257.","productDescription":"108257, 16 p.","ipdsId":"IP-144529","costCenters":[{"id":509,"text":"Office of the Associate Director for Water","active":true,"usgs":true},{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":443551,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecss.2023.108257","text":"Publisher Index Page"},{"id":417021,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Delaware, New Jersey, Pennsylvania","otherGeospatial":"Delaware Bay Estuary","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -75.11619955096559,\n              38.73763237303737\n            ],\n            [\n              -74.81060422137368,\n              39.208395097691294\n            ],\n            [\n              -74.91812850400805,\n              39.25661375840713\n            ],\n            [\n              -75.01433444110185,\n              39.41418851915901\n            ],\n            [\n              -75.23504217914052,\n              39.44041644236643\n            ],\n            [\n              -75.38218067116583,\n              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Center","active":true,"usgs":true}],"preferred":true,"id":872579,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Warner, John C. 0000-0002-3734-8903 jcwarner@usgs.gov","orcid":"https://orcid.org/0000-0002-3734-8903","contributorId":258015,"corporation":false,"usgs":true,"family":"Warner","given":"John","email":"jcwarner@usgs.gov","middleInitial":"C.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":872580,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Russell, Kendra L. 0000-0002-3046-7440","orcid":"https://orcid.org/0000-0002-3046-7440","contributorId":218135,"corporation":false,"usgs":true,"family":"Russell","given":"Kendra","email":"","middleInitial":"L.","affiliations":[{"id":509,"text":"Office of the Associate Director for Water","active":true,"usgs":true}],"preferred":true,"id":872581,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70246609,"text":"70246609 - 2023 - Environmental, morphological, and molecular data reveal a new species of freshwater mussel, Strophitus howellsi, endemic to the Edwards Plateau in Texas","interactions":[],"lastModifiedDate":"2023-10-11T15:32:56.36612","indexId":"70246609","displayToPublicDate":"2023-05-15T06:39:00","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1324,"text":"Conservation Genetics","active":true,"publicationSubtype":{"id":10}},"title":"Environmental, morphological, and molecular data reveal a new species of freshwater mussel, Strophitus howellsi, endemic to the Edwards Plateau in Texas","docAbstract":"<div id=\"Abs1-section\" class=\"c-article-section\"><div id=\"Abs1-content\" class=\"c-article-section__content\"><p>Freshwater mussels are considered the most imperiled group of organisms in North America and systematics research has played an integral role in the development and implementation of their conservation. Despite the importance of systematics in conservation planning, the evolutionary relationships between many mussel taxa remain poorly explored, clearly illustrated by<span>&nbsp;</span><i>Strophitus undulatus</i>. This species is wide-ranging, occurring in streams across the United States and Canada with a disjunct population in the Colorado River drainage in central Texas. The widespread distribution of<span>&nbsp;</span><i>S. undulatus</i>, as well as high intraspecific morphological variation, has led previous authors to doubt the taxon is representative of a single species. In this study, we set out to investigate species boundaries in<span>&nbsp;</span><i>S. undulatus</i><span>&nbsp;</span>by integrating environmental, molecular, and morphological datasets. Molecular and morphological data supported<span>&nbsp;</span><i>S. undulatus</i><span>&nbsp;</span>from the Colorado River as distinct, which was supplemented by a species distribution modeling approach, suggesting potential adaptation to Edwards Plateau streams has contributed to speciation. Given our findings, we formally describe a new species of freshwater mussel,<span>&nbsp;</span><i>Strophitus howellsi</i>, endemic to streams along the Edwards Plateau in the Colorado River drainage. A conservation assessment of<span>&nbsp;</span><i>S. howellsi</i><span>&nbsp;</span>suggests the species is extremely rare within a highly restricted distribution and may warrant future recovery actions. Our findings build on a growing body of literature highlighting aquatic endemism along the Edwards Plateau and have significant conservation implications for freshwater mussels in Texas.</p></div></div>","language":"English","publisher":"Springer","doi":"10.1007/s10592-023-01529-y","usgsCitation":"Smith, C.H., Kiser, A., Johnson, N., and Randklev, C.R., 2023, Environmental, morphological, and molecular data reveal a new species of freshwater mussel, Strophitus howellsi, endemic to the Edwards Plateau in Texas: Conservation Genetics, v. 24, p. 629-647, https://doi.org/10.1007/s10592-023-01529-y.","productDescription":"19 p.; Data Release","startPage":"629","endPage":"647","ipdsId":"IP-141064","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":419358,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9KVVX0Q","text":"Molecular, morphological, and distributional data supporting the recognition of an undescribed freshwater mussel endemic to the Edwards Plateau in the Colorado River basin","linkFileType":{"id":5,"text":"html"}},{"id":418851,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"24","noUsgsAuthors":false,"publicationDate":"2023-05-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Smith, Chase H. 0000-0002-1499-0311","orcid":"https://orcid.org/0000-0002-1499-0311","contributorId":225140,"corporation":false,"usgs":false,"family":"Smith","given":"Chase","email":"","middleInitial":"H.","affiliations":[{"id":13716,"text":"Baylor University","active":true,"usgs":false}],"preferred":false,"id":877329,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kiser, Alexander H.","contributorId":291859,"corporation":false,"usgs":false,"family":"Kiser","given":"Alexander H.","affiliations":[{"id":36313,"text":"Texas A&M","active":true,"usgs":false}],"preferred":false,"id":877330,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Johnson, Nathan 0000-0001-5167-1988","orcid":"https://orcid.org/0000-0001-5167-1988","contributorId":210319,"corporation":false,"usgs":true,"family":"Johnson","given":"Nathan","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":877331,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Randklev, Charles R.","contributorId":202530,"corporation":false,"usgs":false,"family":"Randklev","given":"Charles","email":"","middleInitial":"R.","affiliations":[{"id":36313,"text":"Texas A&M","active":true,"usgs":false}],"preferred":false,"id":877332,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70244207,"text":"70244207 - 2023 - Implications of fire-induced evapotranspiration shifts for recharge-runoff generation and vegetation conversion in the western United States","interactions":[],"lastModifiedDate":"2023-06-07T11:41:27.80442","indexId":"70244207","displayToPublicDate":"2023-05-15T06:37:47","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5836,"text":"Journal of Hydrology X","onlineIssn":"2589-9155","active":true,"publicationSubtype":{"id":10}},"title":"Implications of fire-induced evapotranspiration shifts for recharge-runoff generation and vegetation conversion in the western United States","docAbstract":"<div id=\"abstracts\" class=\"Abstracts u-font-gulliver text-s\"><div id=\"ab010\" class=\"abstract author\"><div id=\"as010\"><p id=\"sp0010\">Wildfire has been shown to increase, decrease, or have no detectable effect on actual evapotranspiration (ETa) fluxes in the western United States. Where disturbance-induced shifts are significant, source-water hydrology may be impacted as ETa constitutes the largest outgoing water flux in much of the arid West. We conducted pixel-scale analysis of 30-m ETa data and various meteorologic and landscape variables at 13 burn scars to understand how wildfire disturbance impacted hillslope-to-burn scar-scale hydrology and vegetation conversion. Significant fire-induced ETa reductions (between approximately −15 to −50%) were detected at nine burn scars through the tenth post-fire year, while ETa recovery rate varied substantially by ecoregion and pre-fire vegetation type. Along elevation gradients, both climate and land disturbance influenced the location of runoff/recharge generation zones, and more net water was generated from a snow-dominated burn scar in dry post-fire years than in wet pre-fire years. However, especially in arid locations where ETa is water-limited, compensatory ETa pathways may be more likely to dampen fire effects on total basin water yield where intact vegetation is located between the disturbance footprint and the basin outlet. Relationships between post-fire ETa shifts and early-successional vegetation conversion were also tracked. The majority of burn scars with significant fire-induced ETa reductions experienced conversion patterns typical of the western United States following stand-replacing disturbance, with forests converting to shrub/scrub and/or grassland/herbaceous cover through at least the end of the study period (eight to 15&nbsp;years depending on date of the fire event). This could have important implications for high-elevation, snow-dominated watersheds – some of the most critical source water areas - as previous research indicates that wildfire activity is moving upslope and into vegetation communities that have not evolved to withstand fire. Finally, we show that much of the Colorado River Basin’s high-yield source water areas are vulnerable to the fire-induced ETa reductions and vegetation conversion observed herein. As such, water managers in the Colorado River Basin can anticipate changes in burn scar hydrology and snowpack mechanics following fire disturbance.</p></div></div></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2023.129646","usgsCitation":"Collar, N.M., Ebel, B., Saxe, S., Rust, A.J., and Hogue, T.S., 2023, Implications of fire-induced evapotranspiration shifts for recharge-runoff generation and vegetation conversion in the western United States: Journal of Hydrology X, v. 621, 129646, 18 p., https://doi.org/10.1016/j.jhydrol.2023.129646.","productDescription":"129646, 18 p.","ipdsId":"IP-141951","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":435336,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9YWPIBM","text":"USGS data release","linkHelpText":"Data supporting 'Linking fire-induced evapotranspiration shifts to streamflow magnitude and timing in the western United States'"},{"id":417902,"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              -126.3581885309159,\n              49.8142776364713\n            ],\n            [\n              -126.3581885309159,\n              29.360204506235704\n            ],\n            [\n              -102.28648531251552,\n              29.360204506235704\n            ],\n            [\n              -102.28648531251552,\n              49.8142776364713\n            ],\n            [\n              -126.3581885309159,\n              49.8142776364713\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"621","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Collar, Natalie M. 0000-0003-4711-0090","orcid":"https://orcid.org/0000-0003-4711-0090","contributorId":306155,"corporation":false,"usgs":false,"family":"Collar","given":"Natalie","email":"","middleInitial":"M.","affiliations":[{"id":66376,"text":"Colorado School of Mines, Department of Civil and Environmental Engineering","active":true,"usgs":false}],"preferred":false,"id":874865,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ebel, Brian A. 0000-0002-5413-3963","orcid":"https://orcid.org/0000-0002-5413-3963","contributorId":211845,"corporation":false,"usgs":true,"family":"Ebel","given":"Brian A.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":874866,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Saxe, Samuel 0000-0003-1151-8908","orcid":"https://orcid.org/0000-0003-1151-8908","contributorId":215753,"corporation":false,"usgs":true,"family":"Saxe","given":"Samuel","email":"","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":874867,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rust, Ashley J.","contributorId":219575,"corporation":false,"usgs":false,"family":"Rust","given":"Ashley","email":"","middleInitial":"J.","affiliations":[{"id":6606,"text":"Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":874868,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hogue, Terri S.","contributorId":205175,"corporation":false,"usgs":false,"family":"Hogue","given":"Terri","email":"","middleInitial":"S.","affiliations":[{"id":6606,"text":"Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":874869,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70251083,"text":"70251083 - 2023 - Named landforms of the World: A geomorphological and physiographic compilation","interactions":[],"lastModifiedDate":"2024-01-22T12:40:58.278113","indexId":"70251083","displayToPublicDate":"2023-05-15T06:37:44","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":17131,"text":"Annals of the AAG","active":true,"publicationSubtype":{"id":10}},"title":"Named landforms of the World: A geomorphological and physiographic compilation","docAbstract":"<div class=\"hlFld-Abstract\"><p class=\"first last\">Prior to the current era of digital geomorphological mapping, global and regional-scale land surface characterization was advanced by qualitative interpretations that relied on human visualization aided by disciplinary knowledge of geophysical processes combined with extensive field study. In the early twentieth century, Fenneman proposed to devise systematic physiographic divisions of the United States and in 1916 produced what is still regarded as an authoritative map of these divisions. His physiographic regions were developed to provide context when describing land surface characteristics of smaller areas using well-known regional characteristics and descriptors. In 1968, geographer Richard E. Murphy published a large-format map of the “Landforms of the World” to fill a gap in the suite of standard classroom maps. In 1990, the British geomorphologist E. M. Bridges published<span>&nbsp;</span><i>World Geomorphology</i>, providing the first global treatment and description of divisions, provinces, and sections—the same hierarchical land partitioning concepts that Fenneman used decades earlier. In the twenty-first century, geographic information systems (GIS) technologies are nearly ubiquitous, yet neither Murphy’s nor Bridges’s work existed as GIS data. To further illuminate their pioneering work, we (1) recompiled Murphy’s landforms as a spatial combination of modern existing data layers, and (2) used the recompiled Murphy’s landforms as a basis for the boundaries of the divisions, provinces, and sections described by Bridges. Our aggregation yields a new resource, Named Landforms of the World, version 2.0, which provides a reference-level, basemap-quality data layer that can significantly facilitate mapping, assessing, and understanding Earth surface features.</p></div>","language":"English","publisher":"American Association of Geographers","doi":"10.1080/24694452.2023.2200548","usgsCitation":"Frye, C., Sayre, R., Murphy, A., Karagulle, D., Pippi, M., Gilbert, M., and Richards, J., 2023, Named landforms of the World: A geomorphological and physiographic compilation: Annals of the AAG, v. 113, no. 8, p. 1762-1780, https://doi.org/10.1080/24694452.2023.2200548.","productDescription":"19 p.","startPage":"1762","endPage":"1780","ipdsId":"IP-146626","costCenters":[{"id":5055,"text":"Land Change Science","active":true,"usgs":true}],"links":[{"id":443556,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1080/24694452.2023.2200548","text":"Publisher Index Page"},{"id":424672,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"South America","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"MultiPolygon\",\"coordinates\":[[[[-65.5,-55.2],[-66.45,-55.25],[-66.9599,-54.8968],[-67.291,-55.3012],[-68.1486,-55.6118],[-68.64,-55.58],[-69.2321,-55.4991],[-69.9581,-55.1984],[-71.0057,-55.0538],[-72.2639,-54.4951],[-73.2852,-53.9575],[-74.6625,-52.8375],[-73.8381,-53.0474],[-72.4342,-53.7154],[-71.1077,-54.0743],[-70.5918,-53.6158],[-70.2675,-52.9312],[-69.3457,-52.5183],[-68.634,-52.6364],[-68.25,-53.1],[-67.75,-53.85],[-66.45,-54.45],[-65.05,-54.7],[-65.5,-55.2]]],[[[-58.4271,-33.9095],[-58.4954,-34.4315],[-57.2258,-35.288],[-57.3624,-35.9774],[-56.7375,-36.4131],[-56.7883,-36.9016],[-57.7492,-38.1839],[-59.2319,-38.7202],[-61.2375,-38.9284],[-62.336,-38.8277],[-62.1258,-39.4241],[-62.3305,-40.1726],[-62.146,-40.6769],[-62.7458,-41.0288],[-63.7705,-41.1668],[-64.7321,-40.8027],[-65.118,-41.0643],[-64.9786,-42.058],[-64.3034,-42.359],[-63.756,-42.0437],[-63.4581,-42.5631],[-64.3788,-42.8736],[-65.1818,-43.4954],[-65.3288,-44.5014],[-65.5653,-45.0368],[-66.51,-45.0396],[-67.2938,-45.5519],[-67.5806,-46.3018],[-66.5971,-47.0339],[-65.641,-47.2361],[-65.9851,-48.1333],[-67.1662,-48.6973],[-67.8161,-49.8697],[-68.7288,-50.2642],[-69.1385,-50.7325],[-68.8156,-51.7711],[-68.15,-52.35],[-68.5716,-52.2994],[-69.4613,-52.292],[-69.9428,-52.5379],[-70.8451,-52.8992],[-71.0063,-53.8333],[-71.4298,-53.8565],[-72.5579,-53.5314],[-73.7028,-52.8351],[-74.9468,-52.2628],[-75.26,-51.6294],[-74.9766,-51.0434],[-75.4798,-50.3784],[-75.608,-48.6738],[-75.1828,-47.7119],[-74.1266,-46.9393],[-75.6444,-46.6476],[-74.6922,-45.764],[-74.3517,-44.103],[-73.2404,-44.455],[-72.7178,-42.3834],[-73.3889,-42.1175],[-73.7013,-43.3658],[-74.3319,-43.225],[-74.018,-41.7948],[-73.6771,-39.9422],[-73.2176,-39.2587],[-73.5056,-38.2829],[-73.5881,-37.1563],[-73.1667,-37.1238],[-72.5531,-35.5088],[-71.8617,-33.9091],[-71.4385,-32.4189],[-71.6687,-30.9206],[-71.3701,-30.0957],[-71.4899,-28.8614],[-70.9051,-27.6404],[-70.725,-25.7059],[-70.404,-23.629],[-70.0913,-21.3933],[-70.1644,-19.7565],[-70.3726,-18.348],[-71.3753,-17.7738],[-71.462,-17.3635],[-73.4445,-16.3594],[-75.2379,-15.2657],[-76.0092,-14.6493],[-76.4235,-13.8232],[-76.2592,-13.535],[-77.1062,-12.2227],[-78.0922,-10.3777],[-79.037,-8.3866],[-79.4459,-7.9308],[-79.7606,-7.1943],[-80.5375,-6.5417],[-81.25,-6.1368],[-80.9264,-5.6906],[-81.4109,-4.7368],[-81.0997,-4.0364],[-80.3026,-3.4049],[-79.7703,-2.6575],[-79.9866,-2.2208],[-80.3688,-2.6852],[-80.9678,-2.2469],[-80.7648,-1.9651],[-80.9337,-1.0575],[-80.5834,-0.9067],[-80.3993,-0.2837],[-80.0209,0.3603],[-80.0906,0.7684],[-79.5428,0.9829],[-78.8553,1.3809],[-78.9909,1.6914],[-78.6178,1.7664],[-78.6621,2.2674],[-78.4276,2.6296],[-77.9315,2.6966],[-77.5104,3.325],[-77.1277,3.8496],[-77.4963,4.0876],[-77.3076,4.668],[-77.5332,5.5828],[-77.3188,5.8454],[-77.4767,6.6911],[-77.8816,7.2238],[-77.7534,7.7098],[-77.4311,7.6381],[-77.2426,7.9353],[-77.4747,8.5243],[-77.3534,8.6705],[-76.8367,8.6388],[-76.0864,9.3368],[-75.6746,9.4433],[-75.6647,9.774],[-75.4804,10.619],[-74.9069,11.083],[-74.2768,11.102],[-74.1972,11.3105],[-73.4148,11.227],[-72.6278,11.732],[-72.2382,11.9556],[-71.7541,12.4373],[-71.3998,12.376],[-71.1375,12.113],[-71.3316,11.7763],[-71.36,11.54],[-71.9471,11.4233],[-71.6209,10.9695],[-71.6331,10.4465],[-72.0742,9.8657],[-71.6956,9.0723],[-71.2646,9.1372],[-71.04,9.86],[-71.3501,10.2119],[-71.4006,10.969],[-70.1553,11.3755],[-70.2938,11.8468],[-69.9432,12.1623],[-69.5843,11.4596],[-68.883,11.4434],[-68.2333,10.8857],[-68.1941,10.5547],[-67.2963,10.5459],[-66.2279,10.6486],[-65.6552,10.2008],[-64.8905,10.0772],[-64.3295,10.3896],[-64.318,10.6414],[-63.0793,10.7017],[-61.881,10.7156],[-62.7301,10.4203],[-62.3885,9.9482],[-61.5888,9.8731],[-60.8306,9.3813],[-60.6713,8.5802],[-60.1501,8.6028],[-59.7583,8.367],[-59.1017,7.9992],[-58.483,7.3477],[-58.4549,6.8328],[-58.0781,6.8091],[-57.5422,6.3213],[-57.1474,5.9732],[-55.9493,5.7729],[-55.8418,5.9531],[-55.0333,6.0253],[-53.958,5.7566],[-54.4786,4.8968],[-54.3995,4.2126],[-54.0069,3.62],[-54.1817,3.1898],[-54.2697,2.7324],[-54.5248,2.3119],[-54.0881,2.1056],[-53.7785,2.3767],[-53.5548,2.3349],[-53.4185,2.0534],[-52.9397,2.1249],[-52.5564,2.5047],[-52.2493,3.2411],[-51.6578,4.1562],[-51.3172,4.2035],[-51.0698,3.6504],[-50.5089,1.9016],[-49.9741,1.7365],[-49.9471,1.0462],[-50.6993,0.223],[-50.3882,-0.0784],[-48.6206,-0.2355],[-48.5845,-1.2378],[-47.825,-0.5816],[-46.5666,-0.941],[-44.9057,-1.5517],[-44.4176,-2.1378],[-44.5816,-2.6913],[-43.4188,-2.3831],[-41.4727,-2.912],[-39.9787,-2.8731],[-38.5004,-3.7007],[-37.2233,-4.821],[-36.4529,-5.1094],[-35.5978,-5.1495],[-35.2354,-5.4649],[-34.896,-6.7382],[-34.73,-7.3432],[-35.1282,-8.9964],[-35.637,-9.6493],[-37.0465,-11.0407],[-37.6836,-12.1712],[-38.4239,-13.0381],[-38.6739,-13.0577],[-38.9533,-13.7934],[-38.8823,-15.6671],[-39.1611,-17.2084],[-39.2673,-17.8678],[-39.5835,-18.2623],[-39.7608,-19.5991],[-40.7747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America\"}}]}","volume":"113","issue":"8","noUsgsAuthors":false,"publicationDate":"2023-05-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Frye, Charlie","contributorId":267718,"corporation":false,"usgs":false,"family":"Frye","given":"Charlie","affiliations":[{"id":38832,"text":"Esri","active":true,"usgs":false}],"preferred":false,"id":893036,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sayre, Roger 0000-0001-6703-7105","orcid":"https://orcid.org/0000-0001-6703-7105","contributorId":245011,"corporation":false,"usgs":true,"family":"Sayre","given":"Roger","affiliations":[{"id":5055,"text":"Land Change Science","active":true,"usgs":true}],"preferred":true,"id":893037,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Murphy, Alexander","contributorId":333533,"corporation":false,"usgs":false,"family":"Murphy","given":"Alexander","email":"","affiliations":[{"id":6604,"text":"University of Oregon","active":true,"usgs":false}],"preferred":false,"id":893038,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Karagulle, Deniz","contributorId":267719,"corporation":false,"usgs":false,"family":"Karagulle","given":"Deniz","affiliations":[{"id":38832,"text":"Esri","active":true,"usgs":false}],"preferred":false,"id":893039,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pippi, Moira","contributorId":333535,"corporation":false,"usgs":false,"family":"Pippi","given":"Moira","email":"","affiliations":[{"id":79921,"text":"University of Siena","active":true,"usgs":false}],"preferred":false,"id":893040,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gilbert, Mark","contributorId":333536,"corporation":false,"usgs":false,"family":"Gilbert","given":"Mark","email":"","affiliations":[{"id":38832,"text":"Esri","active":true,"usgs":false}],"preferred":false,"id":893041,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Richards, Jaynya","contributorId":333537,"corporation":false,"usgs":false,"family":"Richards","given":"Jaynya","email":"","affiliations":[{"id":38832,"text":"Esri","active":true,"usgs":false}],"preferred":false,"id":893042,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70244098,"text":"70244098 - 2023 - The composition of Io","interactions":[],"lastModifiedDate":"2023-06-02T12:24:46.915589","indexId":"70244098","displayToPublicDate":"2023-05-14T07:21:57","publicationYear":"2023","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"7","title":"The composition of Io","docAbstract":"<div id=\"Abs1-section\" class=\"c-article-section\"><div id=\"Abs1-content\" class=\"c-article-section__content\"><p>Io is unlike any other body in the Solar System making questions about its chemical composition especially interesting and challenging. This chapter examines the many different, but frustratingly indirect, constraints we have on the bulk composition of this restless moon. A detailed consideration of Io’s lavas is used to illustrate how decades of research have bounded, but not pinned down, the chemistry of Io. A self-consistent model for the core, mantle and crust is constructed based on a conventional chondritic composition but exotic alternatives cannot be ruled out. The study of Io’s composition should provide a fertile and exciting realm for future scientists.</p></div></div>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Astrophysics and Space Science Library","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer","doi":"10.1007/978-3-031-25670-7_7","usgsCitation":"Keszthelyi, L.P., and Suer, T., 2023, The composition of Io, chap. 7 <i>of</i> Astrophysics and Space Science Library, p. 211-232, https://doi.org/10.1007/978-3-031-25670-7_7.","productDescription":"22 p.","startPage":"211","endPage":"232","ipdsId":"IP-130085","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":417680,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Io","noUsgsAuthors":false,"publicationDate":"2023-05-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Keszthelyi, Laszlo P. 0000-0003-1879-4331 laz@usgs.gov","orcid":"https://orcid.org/0000-0003-1879-4331","contributorId":227,"corporation":false,"usgs":true,"family":"Keszthelyi","given":"Laszlo","email":"laz@usgs.gov","middleInitial":"P.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":874479,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Suer, Terry-Ann","contributorId":211090,"corporation":false,"usgs":false,"family":"Suer","given":"Terry-Ann","email":"","affiliations":[],"preferred":false,"id":874480,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70243559,"text":"70243559 - 2023 - Trends and population estimate of the threatened Buff-breasted Sandpiper Calidris subruficollis wintering in coastal grasslands of southern Brazil","interactions":[],"lastModifiedDate":"2023-05-12T12:37:33.10837","indexId":"70243559","displayToPublicDate":"2023-05-12T07:30:24","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1048,"text":"Bird Conservation International","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Trends and population estimate of the threatened Buff-breasted Sandpiper <i>Calidris subruficollis</i> wintering in coastal grasslands of southern Brazil","title":"Trends and population estimate of the threatened Buff-breasted Sandpiper Calidris subruficollis wintering in coastal grasslands of southern Brazil","docAbstract":"<p><span>Information about population sizes, trends, and habitat use is key for species conservation and management. The Buff-breasted Sandpiper&nbsp;</span><span class=\"italic\">Calidris subruficollis</span><span>&nbsp;(BBSA) is a long-distance migratory shorebird that breeds in the Arctic and migrates to south-eastern South America, wintering in the grasslands of southern Brazil, Uruguay, and Argentina. Most studies of Nearctic migratory species occur in the Northern Hemisphere, but monitoring these species at non-breeding areas is crucial for conservation during this phase of the annual cycle. Our first objective was to estimate trends of BBSA at four key areas in southern Brazil during the non-breeding season. We surveyed for BBSA and measured vegetation height in most years from 2008/09 to 2019/20. We used hierarchical distance sampling models in which BBSA abundance and density were modelled as a function of vegetation height and corrected for detectability. Next, we used on-the-ground surveys combined with satellite imagery and habitat classification models to estimate BBSA population size in 2019/20 at two major non-breeding areas. We found that abundance and density were negatively affected by increasing vegetation height. Abundance fluctuated five- to eight-fold over the study period, with peaks in the middle of the study (2014/15). We estimated the BBSA wintering population size as 1,201 (95% credible interval [CI]: 637–1,946) birds in Torotama Island and 2,232 (95% CI: 1,199–3,584) in Lagoa do Peixe National Park during the 2019/20 austral summer. Although no pronounced trend was detected, BBSA abundance fluctuated greatly from year to year. Our results demonstrate that only two of the four key areas hold high densities of BBSA and highlight the positive effect of short grass on BBSA numbers. Short-grass coastal habitats used by BBSA are strongly influenced by livestock grazing and climate, and are expected to shrink in size with future development and climatic changes.</span></p>","language":"English","publisher":"Cambridge University Press","doi":"10.1017/S0959270923000138","usgsCitation":"Faria, F.A., Dias, R.A., Bencke, G.A., Bugoni, L., Senner, N.R., de Almeida, J.B., Nunes, G.T., Goncalves, M.S., and Lyons, J.E., 2023, Trends and population estimate of the threatened Buff-breasted Sandpiper Calidris subruficollis wintering in coastal grasslands of southern Brazil: Bird Conservation International, v. 33, E61, https://doi.org/10.1017/S0959270923000138.","productDescription":"E61","ipdsId":"IP-142704","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":443569,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1017/s0959270923000138","text":"Publisher Index 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,{"id":70243557,"text":"70243557 - 2023 - Survival of Common Loon chicks appears unaffected by Bald Eagle recovery in northern Minnesota","interactions":[],"lastModifiedDate":"2023-05-23T14:57:20.200377","indexId":"70243557","displayToPublicDate":"2023-05-12T06:47:04","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":947,"text":"Avian Conservation and Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Survival of Common Loon chicks appears unaffected by Bald Eagle recovery in northern Minnesota","docAbstract":"<p><span>Recovering species are not returning to the same environments or communities from which they disappeared. Conservation researchers and practitioners are thus faced with additional challenges in ensuring species resilience in these rapidly changing ecosystems. Assessing the resilience of species in these novel systems can still be guided by species’ ecology, including knowledge of their population size, life history traits, and behavioral adaptations, as well as the type, strength, and number of ways that they interact with other species in the community. We summarized broad trends of Common Loons (</span><i>Gavia immer</i><span>) breeding at Voyageurs National Park from 1973 to 2009, and evaluated the effects of increased risk from recovering Bald Eagles (</span><i>Haliaeetus leucocephalus</i><span>) on chick survival from 2004 to 2006. Adult Common Loons appear to have increased over time. Using Bayesian survival models that accounted for imperfect detection of unmarked individuals, we determined that chick survival of Common Loons was high from year to year and was unrelated to predation risk from Bald Eagles because chicks in territories closer to active nests did not experience greater mortality than those farther away. We suggest that Common Loon chicks were unaffected by the recovery of this top predator during the three years of sampling. Previous research indicates that Bald Eagles and other predators are an important source of egg losses, but Common Loons can compensate by re-nesting. Despite current uncertainties from anthropogenic threats, knowledge of a species’ ecology remains instrumental in determining its resilience during recovery.</span></p>","language":"English","publisher":"Society of Canadian Ornithologists","doi":"10.5751/ACE-02395-180107","usgsCitation":"Cruz, J., Windels, S.K., Thogmartin, W.E., Crimmins, S.M., and Zuckerberg, B., 2023, Survival of Common Loon chicks appears unaffected by Bald Eagle recovery in northern Minnesota: Avian Conservation and Ecology, v. 18, no. 1, 7, 10 p., https://doi.org/10.5751/ACE-02395-180107.","productDescription":"7, 10 p.","ipdsId":"IP-139148","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":443574,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5751/ace-02395-180107","text":"Publisher Index 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K.","contributorId":182422,"corporation":false,"usgs":false,"family":"Windels","given":"Steve","email":"","middleInitial":"K.","affiliations":[{"id":18939,"text":"Voyageurs National Park","active":true,"usgs":false}],"preferred":false,"id":872357,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thogmartin, Wayne E. 0000-0002-2384-4279 wthogmartin@usgs.gov","orcid":"https://orcid.org/0000-0002-2384-4279","contributorId":2545,"corporation":false,"usgs":true,"family":"Thogmartin","given":"Wayne","email":"wthogmartin@usgs.gov","middleInitial":"E.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":872358,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Crimmins, Shawn M. 0000-0001-6229-5543 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,{"id":70249210,"text":"70249210 - 2023 - Machine-learning model to delineate sub-surface agricultural drainage from satellite imagery","interactions":[],"lastModifiedDate":"2023-10-02T11:56:19.176955","indexId":"70249210","displayToPublicDate":"2023-05-11T06:54:29","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2262,"text":"Journal of Environmental Quality","active":true,"publicationSubtype":{"id":10}},"title":"Machine-learning model to delineate sub-surface agricultural drainage from satellite imagery","docAbstract":"<div class=\"abstract-group  metis-abstract\"><div class=\"article-section__content en main\"><p>Knowing subsurface drainage (tile-drain) extent is integral to understanding how landscapes respond to precipitation events and subsequent days of drying, as well as how soil characteristics and land management influence stream response. Consequently, a time series of tile-drain extent would inform one aspect of land management that complicates our ability to explain streamflow and water-quality as a function of climate variability or conservation management. We trained a UNet machine-learning model, a convolutional neural network designed to highlight objects of interest within an image, to delineate tile-drain networks in panchromatic satellite imagery without additional data on soils, topography, or historical tile-drain extent. This was done by training the model to match the accuracy of human experts manually tracing the surface representation of tile drains in satellite imagery. Our approach began with a library of images that were used to train and quantify the accuracy of the model, with model performance tested on imagery from two areas that were not used to train the model. Satellite imagery included acquisition dates from 2008 to 2020. Training imagery was from agricultural areas within the US Great Lakes basin. Validation imagery was from the upper Maumee River, tributary to western Lake Erie, and an Indiana, Ohio-River headwater tributary. Our analysis of the satellite imagery paired with meteorological and soil data found that during spring, a combination of relatively high solar radiation, intermediate soil-water content and bare fields enabled the best model performance. Each area of interest was heavily tile-drained, where better understanding the movement of water, nutrients, and sediment from fields to downstream water bodies is key to managing harmful algal blooms and hypoxia. The trained UNet model successfully identified tile drains visible in the validation imagery with an accuracy of 93%–96% and balanced accuracy of 52%–54%, similar to performance for training data (95% and 63%, respectively). Model performance will benefit from ongoing contributions to the training library.</p></div></div>","language":"English","publisher":"Wiley","doi":"10.1002/jeq2.20493","usgsCitation":"Redoloza, F.S., Williamson, T.N., Headman, A.O., and Allred, B.J., 2023, Machine-learning model to delineate sub-surface agricultural drainage from satellite imagery: Journal of Environmental Quality, v. 52, no. 4, p. 907-921, https://doi.org/10.1002/jeq2.20493.","productDescription":"15 p.","startPage":"907","endPage":"921","ipdsId":"IP-139310","costCenters":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true},{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":443585,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/jeq2.20493","text":"Publisher Index Page"},{"id":435340,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9RHKPLS","text":"USGS data release","linkHelpText":"Continuous meteorological and soil data to support understanding of nutrient and sediment loads from overland and subsurface-tile flow at paired edge-of-field agricultural sites, 2015&amp;amp;amp;amp;ndash;21, Black Creek watershed, near Harlan, Indiana, USA"},{"id":435339,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P96MLCJD","text":"USGS data release","linkHelpText":"Meteorological data from edge-of-field sites in Michigan and Wisconsin, 2015-18"},{"id":435338,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9KSZ382","text":"USGS data release","linkHelpText":"Machine learning with satellite imagery to document the historical transition from topographic to dense sub-surface agricultural drainage networks (tile drains)"},{"id":421456,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Indiana, Michigan, Ohio, Wisconsin","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"MultiPolygon\",\"coordinates\":[[[[-84.820157,39.10548],[-84.816506,38.80532],[-85.448862,38.713368],[-85.415272,38.555416],[-85.816164,38.282969],[-86.042354,37.958018],[-86.33281,38.182938],[-86.634271,37.843845],[-86.810913,37.99715],[-87.065388,37.810481],[-87.402632,37.942267],[-88.051771,37.813761],[-87.938727,38.289264],[-87.496494,38.742728],[-87.632874,39.11055],[-87.531355,39.436656],[-87.524844,41.691635],[-87.187651,41.629653],[-86.824828,41.76024],[-86.321803,42.310743],[-86.226305,42.988284],[-86.540916,43.633158],[-86.25395,44.64808],[-86.066745,44.905685],[-85.780439,44.977932],[-85.540497,45.210169],[-85.641652,44.810816],[-85.520205,44.960347],[-85.477423,44.813781],[-85.355478,45.282774],[-84.91585,45.393115],[-85.069573,45.459239],[-85.079528,45.617083],[-84.94565,45.708621],[-85.011433,45.757962],[-84.774156,45.788918],[-83.488826,45.355872],[-83.316118,45.141958],[-83.435822,45.000012],[-83.277213,44.7167],[-83.335248,44.357995],[-83.890145,43.934672],[-83.909479,43.672622],[-83.618602,43.628891],[-83.227093,43.981003],[-82.915976,44.070503],[-82.643166,43.852468],[-82.423086,42.988728],[-82.509935,42.637294],[-82.648776,42.550401],[-82.630922,42.64211],[-82.780817,42.652232],[-83.40822,41.832654],[-83.37573,41.686647],[-82.481214,41.381342],[-81.69325,41.514161],[-80.533774,41.973475],[-80.518991,40.638801],[-80.667957,40.582496],[-80.619297,40.26517],[-80.88036,39.620706],[-81.656138,39.277355],[-81.874857,38.881174],[-82.068864,38.984878],[-82.318111,38.457876],[-82.569368,38.406258],[-82.923694,38.750076],[-83.301951,38.598178],[-83.512571,38.701716],[-83.679484,38.630036],[-84.212904,38.805707],[-84.445242,39.114461],[-84.820157,39.10548]]],[[[-88.684434,48.115785],[-88.447236,48.182916],[-89.022736,47.858532],[-89.255202,47.876102],[-88.684434,48.115785]]],[[[-90.418136,46.566094],[-88.982483,46.99883],[-88.400224,47.379551],[-87.816958,47.471998],[-87.730804,47.449112],[-88.349952,47.076377],[-88.462349,46.786711],[-88.167373,46.9588],[-87.915943,46.909508],[-87.619747,46.79821],[-87.366767,46.507303],[-86.850111,46.434114],[-86.188024,46.654008],[-84.964652,46.772845],[-84.969464,46.47629],[-84.177428,46.52692],[-84.097766,46.256512],[-84.247687,46.17989],[-83.931175,46.017871],[-83.63498,46.103953],[-83.49484,45.999541],[-84.345451,45.946569],[-84.656567,46.052654],[-84.820557,45.868293],[-85.047028,46.020603],[-85.528403,46.087121],[-85.663966,45.967013],[-86.278007,45.942057],[-86.687208,45.634253],[-86.532989,45.882665],[-86.92106,45.697868],[-87.018902,45.838886],[-88.027103,44.578992],[-87.943801,44.529693],[-87.428144,44.890738],[-87.021088,45.296541],[-87.73063,43.893862],[-87.910172,43.236634],[-87.800477,42.49192],[-90.614589,42.508053],[-91.078097,42.806526],[-91.177728,43.118733],[-91.062562,43.243165],[-91.375142,43.944289],[-92.787906,44.737432],[-92.802056,45.057423],[-92.650422,45.398507],[-92.883987,45.65487],[-92.683924,45.903939],[-92.319329,46.069289],[-92.291647,46.604649],[-92.178891,46.716741],[-91.781928,46.697604],[-90.880358,46.957661],[-90.78804,46.844886],[-90.920813,46.637432],[-90.418136,46.566094]]],[[[-86.880572,45.331467],[-86.956192,45.351179],[-86.82177,45.427602],[-86.880572,45.331467]]]]},\"properties\":{\"name\":\"Indiana\",\"nation\":\"USA  \"}}]}","volume":"52","issue":"4","noUsgsAuthors":false,"publicationDate":"2023-05-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Redoloza, Fleford Santos 0000-0002-0726-5963","orcid":"https://orcid.org/0000-0002-0726-5963","contributorId":330390,"corporation":false,"usgs":true,"family":"Redoloza","given":"Fleford","email":"","middleInitial":"Santos","affiliations":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":884819,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Williamson, Tanja N. 0000-0002-7639-8495 tnwillia@usgs.gov","orcid":"https://orcid.org/0000-0002-7639-8495","contributorId":198329,"corporation":false,"usgs":true,"family":"Williamson","given":"Tanja","email":"tnwillia@usgs.gov","middleInitial":"N.","affiliations":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":884820,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Headman, Alexander O. 0000-0003-0034-3970 aheadman@usgs.gov","orcid":"https://orcid.org/0000-0003-0034-3970","contributorId":196986,"corporation":false,"usgs":true,"family":"Headman","given":"Alexander","email":"aheadman@usgs.gov","middleInitial":"O.","affiliations":[],"preferred":true,"id":884821,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Allred, Barry J.","contributorId":212023,"corporation":false,"usgs":false,"family":"Allred","given":"Barry","email":"","middleInitial":"J.","affiliations":[{"id":38388,"text":"USDA, Agricultural Research Service","active":true,"usgs":false}],"preferred":false,"id":884822,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70243527,"text":"70243527 - 2023 - The use of historical data and global climate models to assess historical and future surface water and groundwater availability in the Trinity River Basin in Texas","interactions":[],"lastModifiedDate":"2023-05-11T12:00:01.116319","indexId":"70243527","displayToPublicDate":"2023-05-11T06:53:00","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3536,"text":"Texas Water Journal","active":true,"publicationSubtype":{"id":10}},"title":"The use of historical data and global climate models to assess historical and future surface water and groundwater availability in the Trinity River Basin in Texas","docAbstract":"<p><span>This paper describes the results of a study that was done by the USGS to assess recent (2017) water availability, forecast long-term trends in water availability, assess changes in water availability, and forecast future water availability in the Trinity River Basin in Texas. The Trinity River Basin surface water model and Trinity River alluvium aquifer (TRAA) groundwater model were created to evaluate future conditions under different global climate models (GCM). The results of this study show minimal overall changes in water availability for both surface water and groundwater. Trend analyses using historical data (1900–2017) indicated an increase of annual precipitation on the watersheds that drain into the reservoirs in Regional Water Planning Group C. However, the Trinity River Basin surface water model GCM ensemble mean annual precipitation indicates a downward trend, resulting in a downward trend in surface runoff. Additionally, the GCM ensemble mean for the Trinity River Basin surface water model and the TRAA groundwater model both indicate a downward trend in recharge while the TRAA model GCM ensemble mean indicates an upward trend in the amount of groundwater leaving the aquifer to rivers and streams resulting in an upward trend of cumulative storage change.</span></p>","language":"English","publisher":"Texas Water Journal","doi":"10.21423/twj.v14i1.7146","usgsCitation":"Milmo, M.J., McDowell, J., Yesildirek, M.V., and Harwell, G.R., 2023, The use of historical data and global climate models to assess historical and future surface water and groundwater availability in the Trinity River Basin in Texas: Texas Water Journal, v. 14, p. 34-61, https://doi.org/10.21423/twj.v14i1.7146.","productDescription":"28 p.","startPage":"34","endPage":"61","ipdsId":"IP-126619","costCenters":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":443587,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"http://dx.doi.org/10.21423/twj.v14i1.7146","text":"Publisher Index Page"},{"id":435342,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9BVOEJ3","text":"USGS data release","linkHelpText":"Hydrologic simulations using projected climate data as input to the Precipitation-Runoff Modeling System (PRMS) for the Trinity River Basin Integrated Water Availability Assessment, Texas, 2023"},{"id":435341,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9XO5F9G","text":"USGS data release","linkHelpText":"MODFLOW-NWT model used to assess historical and future trends in groundwater availability in the Trinity River alluvium aquifer, Texas"},{"id":416955,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Texas","otherGeospatial":"Trinity River Basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -95.0568823566713,\n              29.605130308347057\n            ],\n            [\n              -94.82111695509118,\n              29.47268831477325\n            ],\n            [\n              -94.56341988824927,\n              29.61102156169673\n            ],\n            [\n              -94.98560444456466,\n              31.578939128932277\n            ],\n            [\n              -95.40230608456515,\n              32.304435780613815\n            ],\n            [\n              -95.72579814719658,\n              32.762064472265905\n            ],\n            [\n              -95.93963188351171,\n              33.33195284298357\n            ],\n            [\n              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]\n}","volume":"14","edition":"1","noUsgsAuthors":false,"publicationDate":"2023-03-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Milmo, Molly J. 0000-0001-9074-0982","orcid":"https://orcid.org/0000-0001-9074-0982","contributorId":245854,"corporation":false,"usgs":true,"family":"Milmo","given":"Molly","email":"","middleInitial":"J.","affiliations":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":872223,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McDowell, Jeremy 0000-0002-8132-9806","orcid":"https://orcid.org/0000-0002-8132-9806","contributorId":221296,"corporation":false,"usgs":true,"family":"McDowell","given":"Jeremy","email":"","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":872224,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Yesildirek, Monica Veale 0000-0002-0320-8531","orcid":"https://orcid.org/0000-0002-0320-8531","contributorId":228880,"corporation":false,"usgs":true,"family":"Yesildirek","given":"Monica","email":"","middleInitial":"Veale","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":872225,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Harwell, Glenn R. 0000-0003-4265-2296","orcid":"https://orcid.org/0000-0003-4265-2296","contributorId":205197,"corporation":false,"usgs":true,"family":"Harwell","given":"Glenn","email":"","middleInitial":"R.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":872226,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70243688,"text":"70243688 - 2023 - Exploring the influence of input feature space on CNN-based geomorphic feature extraction from digital terrain data","interactions":[],"lastModifiedDate":"2023-05-17T13:49:27.788978","indexId":"70243688","displayToPublicDate":"2023-05-10T08:48:03","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5026,"text":"Earth and Space Science","active":true,"publicationSubtype":{"id":10}},"title":"Exploring the influence of input feature space on CNN-based geomorphic feature extraction from digital terrain data","docAbstract":"<p><span>Many studies of Earth surface processes and landscape evolution rely on having accurate and extensive data sets of surficial geologic units and landforms. Automated extraction of geomorphic features using deep learning provides an objective way to consistently map landforms over large spatial extents. However, there is no consensus on the optimal input feature space for such analyses. We explore the impact of input feature space for extracting geomorphic features from land surface parameters (LSPs) derived from digital terrain models (DTMs) using convolutional neural network (CNN)-based semantic segmentation deep learning. We compare four input feature space configurations: (a) a three-layer composite consisting of a topographic position index (TPI) calculated using a 50&nbsp;m radius circular window, square root of topographic slope, and TPI calculated using an annulus with a 2&nbsp;m inner radius and 10&nbsp;m outer radius, (b) a single illuminating position hillshade, (c) a multidirectional hillshade, and (d) a slopeshade. We test each feature space input using three deep learning algorithms and four use cases: two with natural features and two with anthropogenic features. The three-layer composite generally provided lower overall losses for the training samples, a higher F1-score for the withheld validation data, and better performance for generalizing to withheld testing data from a new geographic extent. Results suggest that CNN-based deep learning for mapping geomorphic features or landforms from LSPs is sensitive to input feature space. Given the large number of LSPs that can be derived from DTM data and the variety of geomorphic mapping tasks that can be undertaken using CNN-based methods, we argue that additional research focused on feature space considerations is needed and suggest future research directions. We also suggest that the three-layer composite implemented here can offer better performance in comparison to using hillshades or other common terrain visualization surfaces and is, thus, worth considering for different mapping and feature extraction tasks.</span></p>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2023EA002845","usgsCitation":"Maxwell, A.E., Odom, W.E., Shobe, C.M., Doctor, D.H., Bester, M.S., and Ore, T., 2023, Exploring the influence of input feature space on CNN-based geomorphic feature extraction from digital terrain data: Earth and Space Science, v. 10, no. 5, e2023EA002845, 25 p., https://doi.org/10.1029/2023EA002845.","productDescription":"e2023EA002845, 25 p.","ipdsId":"IP-150908","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":443593,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2023ea002845","text":"Publisher Index Page"},{"id":417130,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"10","issue":"5","noUsgsAuthors":false,"publicationDate":"2023-05-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Maxwell, Aaron E.","contributorId":305483,"corporation":false,"usgs":false,"family":"Maxwell","given":"Aaron","email":"","middleInitial":"E.","affiliations":[{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":872914,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Odom, William Elijah 0000-0001-8577-5056","orcid":"https://orcid.org/0000-0001-8577-5056","contributorId":292616,"corporation":false,"usgs":true,"family":"Odom","given":"William","email":"","middleInitial":"Elijah","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":872915,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shobe, Charles M.","contributorId":305484,"corporation":false,"usgs":false,"family":"Shobe","given":"Charles","email":"","middleInitial":"M.","affiliations":[{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":872917,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Doctor, Daniel H. 0000-0002-8338-9722 dhdoctor@usgs.gov","orcid":"https://orcid.org/0000-0002-8338-9722","contributorId":2037,"corporation":false,"usgs":true,"family":"Doctor","given":"Daniel","email":"dhdoctor@usgs.gov","middleInitial":"H.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":872918,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bester, Michelle S.","contributorId":305485,"corporation":false,"usgs":false,"family":"Bester","given":"Michelle","email":"","middleInitial":"S.","affiliations":[{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":872920,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ore, Tobi","contributorId":305487,"corporation":false,"usgs":false,"family":"Ore","given":"Tobi","email":"","affiliations":[{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":872921,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70243953,"text":"70243953 - 2023 - Evaluation of Copernicus DEM and comparison to the DEM used for Landsat collection-2 processing","interactions":[],"lastModifiedDate":"2023-06-12T21:50:00.086818","indexId":"70243953","displayToPublicDate":"2023-05-10T07:04:02","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Evaluation of Copernicus DEM and comparison to the DEM used for Landsat collection-2 processing","docAbstract":"<div class=\"html-p\">Having highly accurate and reliable Digital Elevation Models (DEMs) of the Earth’s surface is critical to orthorectify Landsat imagery. Without such accuracy, pixel locations reported in the data are difficult to assure as accurate, especially in more mountainous landscapes, where the orthorectification process is the most challenging. To this end, the Landsat Calibration and Validation Team (Cal/Val) compared the Copernicus DEM (CopDEM) to the DEM that is currently used in Collection-2 processing (called “Collection-2 DEM”). NGS ground-surveyed and lidar-based ICESat-2 points were used, and the CopDEM shows improvement to be less than 1 m globally, except in Asia where the accuracy and resolution of the DEM were greater for the CopDEM compared to the Collection-2 DEM. Along with slightly improved accuracy, the CopDEM showed more consistent results globally due to its virtually seamless source and consistent creation methods throughout the dataset. While CopDEM is virtually seamless, having greater than 99% of their data coming from a single source (Tandem-X), there are significantly more voids in the higher elevations which were mostly filled with SRTM derivatives. The accuracy of the CopDEM fill imagery was also compared to the Collection-2 DEM and the results were very similar, showing that the choice of fill imagery used by CopDEM was appropriate. A qualitative assessment using terrain-corrected products processed with different DEMs and viewing them as anaglyphs to evaluate the DEMs proved useful for assessing orbital path co-registration. While the superiority of the CopDEM was not shown to be definitive by the qualitative method for many of the regions assessed, the CopDEM showed a clear advantage in Northern Russia, where the Collection-2 DEM uses some of the oldest and least accurate datasets in the compilation of the Collection-2 DEM. This paper presents results from the comparison study, along with the justification for proceeding with using the Copernicus DEM in future Landsat processing. As of this writing, the Copernicus DEM is planned to be used in Collection-3 processing, which is anticipated to be released no earlier than 2025.</div>","language":"English","publisher":"MDPI","doi":"10.3390/rs15102509","usgsCitation":"Franks, S., and Rengarajan, R., 2023, Evaluation of Copernicus DEM and comparison to the DEM used for Landsat collection-2 processing: Remote Sensing, v. 15, no. 10, 2509, 28 p., https://doi.org/10.3390/rs15102509.","productDescription":"2509, 28 p.","ipdsId":"IP-151515","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":443596,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs15102509","text":"Publisher Index Page"},{"id":417483,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"15","issue":"10","noUsgsAuthors":false,"publicationDate":"2023-05-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Franks, Shannon 0000-0003-1335-5401","orcid":"https://orcid.org/0000-0003-1335-5401","contributorId":245457,"corporation":false,"usgs":false,"family":"Franks","given":"Shannon","email":"","affiliations":[{"id":49197,"text":"KBR, Contractor to NASA Goddard Space Flight Center","active":true,"usgs":false}],"preferred":false,"id":873893,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rengarajan, Rajagopalan 0000-0003-1860-7110","orcid":"https://orcid.org/0000-0003-1860-7110","contributorId":242014,"corporation":false,"usgs":false,"family":"Rengarajan","given":"Rajagopalan","affiliations":[{"id":48475,"text":"KBR, Contractor to USGS EROS","active":true,"usgs":false}],"preferred":false,"id":873894,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70247879,"text":"70247879 - 2023 - Using seasonal climate scenarios in the ForageAhead annual forage production model for early drought impact assessment","interactions":[],"lastModifiedDate":"2023-08-23T12:01:19.695413","indexId":"70247879","displayToPublicDate":"2023-05-10T06:56:04","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":"Using seasonal climate scenarios in the ForageAhead annual forage production model for early drought impact assessment","docAbstract":"<div class=\"abstract-group  metis-abstract\"><div class=\"article-section__content en main\"><p>High interannual variability of forage production in semiarid grasslands leads to uncertainties when livestock producers make decisions, such as buying additional feed, relocating animals, or using flexible stocking. Within-season predictions of annual forage production (i.e., yearly production) can provide specific boundaries for producers to make these decisions with more information and possibly with higher confidence. In this study, we use a recently developed forage production model, ForageAhead, that uses environmental and seasonal climate variables to estimate the annual forage production as approximated by remotely sensed vegetation data. Because, among other variables, this model uses observed summer climate data, the model output cannot be produced early enough in the year (e.g., spring months) to inform within-season management decisions. To address this issue, we developed summer climate scenarios (e.g., extremely warm and dry and moderately cool and wet) that serve as an input in the model in combination with observed winter and spring climate data from a particular year. The summer climate scenarios used historical summer precipitation and temperature data (1950–2018) categorized into three, five, and seven percentile categories. These percentile values were then combined to represent summer climate scenarios, which were further used as the ForageAhead model input. We tested the optimal number of percentile categories to be used as the model input to obtain accurate prediction of forage production while also minimizing the number of possible temperature and precipitation combinations, which increases with the number of percentile categories. For the 19-year period analysis (2000–2018), we also determined the most and least common scenarios that occurred in the western United States. When using five percentile categories for summer precipitation and temperature, we were able to capture the interannual variability in the spatial extent of abnormally low and high biomass production. The ForageAhead predictions captured similar spatial patterns of forage anomalies as another similar model (Grass-Cast). This method can be made available in a user-friendly automated system that can be used by livestock producers and rangeland managers to inform within-season management decisions. This method can be especially valuable for flexible stocking as it provides a range of possible annual forage production scenarios by the end of May.</p></div></div>","language":"English","publisher":"Wiley","doi":"10.1002/ecs2.4496","usgsCitation":"Podebradska, M., Wylie, B., Hayes, M.J., Bathke, D., Bayissa, Y., Boyte, S., Brown, J.F., and Wardlow, B., 2023, Using seasonal climate scenarios in the ForageAhead annual forage production model for early drought impact assessment: Ecosphere, v. 14, no. 5, e4496, 29 p., https://doi.org/10.1002/ecs2.4496.","productDescription":"e4496, 29 p.","ipdsId":"IP-138855","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":443598,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.4496","text":"Publisher Index Page"},{"id":435343,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9GICV05","text":"USGS data release","linkHelpText":"Using seasonal climate scenarios in the ForageAhead annual forage production model for early drought impact assessment"},{"id":420066,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"14","issue":"5","noUsgsAuthors":false,"publicationDate":"2023-05-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Podebradska, Marketa 0000-0002-3121-4904","orcid":"https://orcid.org/0000-0002-3121-4904","contributorId":218698,"corporation":false,"usgs":false,"family":"Podebradska","given":"Marketa","email":"","affiliations":[{"id":33286,"text":"School of Natural Resources, University of Nebraska-Lincoln","active":true,"usgs":false}],"preferred":false,"id":880846,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wylie, Bruce K. 0000-0002-7374-1083","orcid":"https://orcid.org/0000-0002-7374-1083","contributorId":270258,"corporation":false,"usgs":false,"family":"Wylie","given":"Bruce K.","affiliations":[{"id":56122,"text":"Retired - US Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center","active":true,"usgs":false}],"preferred":false,"id":880853,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hayes, Michael J. 0000-0001-5006-166X","orcid":"https://orcid.org/0000-0001-5006-166X","contributorId":243284,"corporation":false,"usgs":false,"family":"Hayes","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":48673,"text":"School of Natural Resources, University of Nebraska-Lincoln, 811 Hardin Hall, 3310 Holdrege Street, Lincoln, Nebraska 68583-0988","active":true,"usgs":false}],"preferred":false,"id":880851,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bathke, Deborah J.","contributorId":270259,"corporation":false,"usgs":false,"family":"Bathke","given":"Deborah J.","affiliations":[{"id":33286,"text":"School of Natural Resources, University of Nebraska-Lincoln","active":true,"usgs":false}],"preferred":false,"id":880847,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bayissa, Yared A.","contributorId":270260,"corporation":false,"usgs":false,"family":"Bayissa","given":"Yared A.","affiliations":[{"id":56123,"text":"Department of Ecology and Conservation Biology","active":true,"usgs":false}],"preferred":false,"id":880848,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Boyte, Stephen P. 0000-0002-5462-3225","orcid":"https://orcid.org/0000-0002-5462-3225","contributorId":205374,"corporation":false,"usgs":true,"family":"Boyte","given":"Stephen P.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":880849,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Brown, Jesslyn F. 0000-0002-9976-1998 jfbrown@usgs.gov","orcid":"https://orcid.org/0000-0002-9976-1998","contributorId":176609,"corporation":false,"usgs":true,"family":"Brown","given":"Jesslyn","email":"jfbrown@usgs.gov","middleInitial":"F.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":880850,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Wardlow, Brian D.","contributorId":270267,"corporation":false,"usgs":false,"family":"Wardlow","given":"Brian D.","affiliations":[{"id":33286,"text":"School of Natural Resources, University of Nebraska-Lincoln","active":true,"usgs":false}],"preferred":false,"id":880852,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70244299,"text":"70244299 - 2023 - Genetic mark–recapture analysis reveals large annual variation in pre-breeding sex ratio of greater sage-grouse","interactions":[],"lastModifiedDate":"2023-07-26T14:42:40.52539","indexId":"70244299","displayToPublicDate":"2023-05-10T06:37:46","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3766,"text":"Wildlife Biology","active":true,"publicationSubtype":{"id":10}},"title":"Genetic mark–recapture analysis reveals large annual variation in pre-breeding sex ratio of greater sage-grouse","docAbstract":"<div class=\"abstract-group \"><div class=\"article-section__content en main\"><p>Sex ratio, and the extent to which it varies over time, is an important factor in the demography, management, and conservation of wildlife populations. Greater sage-grouse<span>&nbsp;</span><i>Centrocercus urophasianus</i><span>&nbsp;</span>populations in western North America are monitored using counts of males at leks in spring. Population estimates derived from lek-count data typically assume a constant, female-biased sex ratio, yet few rigorous, empirically derived estimates of sex ratio are available to test that assumption. We estimated pre-breeding sex ratio of greater sage-grouse in a peripheral, geographically isolated population in northwestern Colorado during two consecutive winters using closed-population, robust-design, multi-state, genetic mark–recapture models in program MARK. Sex ratio varied markedly between years, with estimates of 3.29 (95% CI: 2.36–4.59) females per male in winter 2012–2013 and 1.54 (95% CI: 1.22–1.95) females per male in winter 2013–2014. Rather than assuming a constant sex ratio, biologists should consider the potential for large annual variation in sex ratio of greater sage-grouse populations when estimating population size or trend from male lek-count data.</p></div></div>","language":"English","publisher":"Wiley","doi":"10.1002/wlb3.01085","usgsCitation":"Shyvers, J.E., Walker, B.L., Oyler-McCance, S.J., Fike, J., and Noon, B.R., 2023, Genetic mark–recapture analysis reveals large annual variation in pre-breeding sex ratio of greater sage-grouse: Wildlife Biology, v. 2023, no. 4, e01085, 10 p., https://doi.org/10.1002/wlb3.01085.","productDescription":"e01085, 10 p.","ipdsId":"IP-126794","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":443604,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/wlb3.01085","text":"Publisher Index Page"},{"id":418044,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"2023","issue":"4","noUsgsAuthors":false,"publicationDate":"2023-05-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Shyvers, Jessica E. 0000-0002-4307-0004","orcid":"https://orcid.org/0000-0002-4307-0004","contributorId":288929,"corporation":false,"usgs":true,"family":"Shyvers","given":"Jessica","email":"","middleInitial":"E.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":875250,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Walker, Brett L","contributorId":248865,"corporation":false,"usgs":false,"family":"Walker","given":"Brett","email":"","middleInitial":"L","affiliations":[{"id":36246,"text":"CPW","active":true,"usgs":false}],"preferred":false,"id":875251,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Oyler-McCance, Sara J. 0000-0003-1599-8769 sara_oyler-mccance@usgs.gov","orcid":"https://orcid.org/0000-0003-1599-8769","contributorId":1973,"corporation":false,"usgs":true,"family":"Oyler-McCance","given":"Sara","email":"sara_oyler-mccance@usgs.gov","middleInitial":"J.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":875252,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fike, Jennifer A. 0000-0001-8797-7823","orcid":"https://orcid.org/0000-0001-8797-7823","contributorId":207268,"corporation":false,"usgs":true,"family":"Fike","given":"Jennifer A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":875253,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Noon, Barry R.","contributorId":198981,"corporation":false,"usgs":false,"family":"Noon","given":"Barry","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":875254,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
]}