{"pageNumber":"27","pageRowStart":"650","pageSize":"25","recordCount":40777,"records":[{"id":70268390,"text":"70268390 - 2025 - Rapid emplacement of the Keaiwa Lava Flow of 1823 from the Great Crack in the Southwest Rift Zone of Kilauea volcano","interactions":[],"lastModifiedDate":"2025-06-24T14:27:46.198157","indexId":"70268390","displayToPublicDate":"2025-06-19T09:20:50","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2499,"text":"Journal of Volcanology and Geothermal Research","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Rapid emplacement of the Keaīwa Lava Flow of 1823 from the Great Crack in the Southwest Rift Zone of Kīlauea volcano","title":"Rapid emplacement of the Keaiwa Lava Flow of 1823 from the Great Crack in the Southwest Rift Zone of Kilauea volcano","docAbstract":"<p><span>The Keaīwa Lava Flow of 1823 in the Southwest Rift Zone of Kīlauea volcano is unusual for its expansive pāhoehoe sheet flow morphology and lack of constructive vent topography, despite having a similar tholeiitic basalt composition to other lavas erupted from Kīlauea. This lava flow issued from a&nbsp;∼10-km-long continuous fissure now known as the Great Crack, and has an unusually thin sheet flow morphology with margin thicknesses of ∼15–110&nbsp;cm (average of 42&nbsp;cm). Based on field observations of the lava flow at its fissure vent (e.g., drain-back features), we propose that the Great Crack formed, or at least significantly widened, just prior to and syn-eruptively with this 1823 eruption. The absence of pyroclastic cones or spatter ramparts indicates that the eruption consisted of a rapid outpouring of relatively degassed lava as the fissure unzipped. The rapidly moving lava flow overtopped pre-existing tumuli and scoria cones (e.g., Lava Plastered Cones) up to ∼10&nbsp;m tall. Glass and whole-rock chemistry yield homogeneous compositions for the lavas erupted from the Great Crack, with glass compositions of 6.40&nbsp;±&nbsp;0.10&nbsp;wt% MgO and whole-rock compositions of 7.39&nbsp;±&nbsp;0.07&nbsp;wt% MgO. Lava pads erupted from a short western fissure system are richer in mafic minerals (e.g., olivine and clinopyroxene), and show slightly more MgO-rich whole-rock compositions (7.79&nbsp;±&nbsp;0.05&nbsp;wt%). MgO-in-glass thermometry on juvenile spatter yield eruption temperatures of 1153&nbsp;±&nbsp;13°C that are typical of Kīlauea lavas. Thus, the extensive sheet-like lava flow morphology is not a direct consequence of unusual magmatic or rheological conditions (i.e., low viscosity). Instead, the flow morphology is associated with high effusion rates caused by sudden drainage of uprift magma as it erupted from the Great Crack. Lava flow modeling on a 2-m-resolution digital elevation model indicates that a minimum bulk effusion rate of ∼5800&nbsp;m</span><sup>3</sup><span>/s (∼3500&nbsp;m</span><sup>3</sup><span>/s dense rock equivalent) and a minimum flow velocity of ∼11&nbsp;m/s are required for the lava flow to overcome the topography of the Lava Plastered Cones. This effusion rate is among the highest inferred for eruptions in Hawaiʻi and around the world. This study highlights a less frequent eruption style at Hawaiian volcanoes characterized by a sudden outpouring of lava from an unusual fissure system. Local eyewitness accounts indicate that the 1823 eruption was preceded by seismicity. Given the complex magmatic-volcanic-tectonic relations across Kīlauea, we speculate that the south flank could have slipped over one or more events that ultimately triggered unzipping of the Great Crack and passive release of briefly stored uprift magma. An eruption similar to 1823 at Kīlauea or Mauna Loa, with an eruptive timeframe that could be as short as an hour, with high effusion rates and rapid flow front velocities, would not easily allow for a timely response.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jvolgeores.2025.108391","usgsCitation":"Tonato, A., Shea, T., Downs, D.T., and Kelfoun, K., 2025, Rapid emplacement of the Keaiwa Lava Flow of 1823 from the Great Crack in the Southwest Rift Zone of Kilauea volcano: Journal of Volcanology and Geothermal Research, v. 466, 108391, 18 p., https://doi.org/10.1016/j.jvolgeores.2025.108391.","productDescription":"108391, 18 p.","ipdsId":"IP-169862","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":494405,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jvolgeores.2025.108391","text":"Publisher Index Page"},{"id":491181,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Great Crack in the Southwest Rift Zone of Kīlauea volcano, Keaīwa Lava Flow","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -155.2184297752859,\n              19.437317498221987\n            ],\n            [\n              -155.5,\n              19.437317498221987\n            ],\n            [\n              -155.5,\n              19.1667\n            ],\n            [\n              -155.2184297752859,\n              19.1667\n            ],\n            [\n              -155.2184297752859,\n              19.437317498221987\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"466","noUsgsAuthors":false,"publicationDate":"2025-06-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Tonato, Andrea","contributorId":352882,"corporation":false,"usgs":false,"family":"Tonato","given":"Andrea","affiliations":[{"id":64253,"text":"University of Hawaiʻi at Mānoa","active":true,"usgs":false}],"preferred":false,"id":941184,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shea, Thomas","contributorId":236886,"corporation":false,"usgs":false,"family":"Shea","given":"Thomas","affiliations":[{"id":47560,"text":"University of Hawaii Manoa","active":true,"usgs":false}],"preferred":false,"id":941185,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Downs, Drew T. 0000-0002-9056-1404 ddowns@usgs.gov","orcid":"https://orcid.org/0000-0002-9056-1404","contributorId":173516,"corporation":false,"usgs":true,"family":"Downs","given":"Drew","email":"ddowns@usgs.gov","middleInitial":"T.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":941186,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kelfoun, Karim","contributorId":333750,"corporation":false,"usgs":false,"family":"Kelfoun","given":"Karim","email":"","affiliations":[{"id":79967,"text":"Laboratoire Magmas et Volcans, Université Clermont Auvergne, Clermont-Ferrand, France","active":true,"usgs":false}],"preferred":false,"id":941187,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70269030,"text":"70269030 - 2025 - Navigating the possibilities and pitfalls of biocrust recovery in a changing climate","interactions":[],"lastModifiedDate":"2025-07-14T13:33:03.584001","indexId":"70269030","displayToPublicDate":"2025-06-19T08:31:26","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":724,"text":"American Journal of Botany","active":true,"publicationSubtype":{"id":10}},"title":"Navigating the possibilities and pitfalls of biocrust recovery in a changing climate","docAbstract":"<p><span>Biological soil crusts are complex communities composed of lichens, mosses, bacteria, and cyanobacteria that create a living skin on the soil surface across drylands worldwide. Although small in size, the vast area that biocrusts cover and the critical functions they provide make them a cornerstone of dryland health and resiliency. In addition to being important, biocrusts are exceptionally vulnerable to certain types of disturbance. Although they can withstand a wide range of temperatures and long periods without precipitation, biocrusts are highly sensitive to land-use change and are vulnerable to physical and compressional disturbance (i.e., trampling, vehicles, cattle, heavy machinery). In the face of these disturbances, a critical, long-standing question of interest to dryland ecologists is: Can biocrusts recover following disturbance without active intervention. If so, how long does it take? Early estimates of biocrust recovery suggested recovery can be incredibly slow (on the order of thousands of years), with more modern studies finding potential for faster recovery, especially with intervention. Multiple lines of evidence agree that recovery is context dependent, differing across climates, soils, and with the types of disturbance and biocrust. Additionally, active restoration of biocrusts is becoming more common as tractable strategies are developed for facilitating the establishment of biocrusts after disturbance. Here, we add to the body of knowledge about biocrust recovery following disturbances by reviewing recovery patterns, their connection to climate change, considerations for recovery in changing climates, and the role of restoration.</span></p>","language":"English","publisher":"Botanical Society of AMerica","doi":"10.1002/ajb2.70055","usgsCitation":"Phillips, M.L., Young, K.E., Lauria, C.M., Jech, S., Giraldo-Silva, A., and Reed, S., 2025, Navigating the possibilities and pitfalls of biocrust recovery in a changing climate: American Journal of Botany, v. 112, e70055, 8 p., https://doi.org/10.1002/ajb2.70055.","productDescription":"e70055, 8 p.","ipdsId":"IP-176307","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":492481,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ajb2.70055","text":"Publisher Index Page"},{"id":492193,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"112","noUsgsAuthors":false,"publicationDate":"2025-06-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Phillips, Michala Lee 0000-0001-7005-8740","orcid":"https://orcid.org/0000-0001-7005-8740","contributorId":245186,"corporation":false,"usgs":true,"family":"Phillips","given":"Michala","email":"","middleInitial":"Lee","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":942951,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Young, Kristina E.","contributorId":210572,"corporation":false,"usgs":false,"family":"Young","given":"Kristina","email":"","middleInitial":"E.","affiliations":[{"id":38116,"text":"Department of Biological Sciences, University of Texas at El Paso, El Paso, TX 79902, USA","active":true,"usgs":false}],"preferred":false,"id":942952,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lauria, Cara Marie 0000-0001-8914-8041","orcid":"https://orcid.org/0000-0001-8914-8041","contributorId":271066,"corporation":false,"usgs":true,"family":"Lauria","given":"Cara","email":"","middleInitial":"Marie","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":942953,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jech, Sierra","contributorId":292726,"corporation":false,"usgs":false,"family":"Jech","given":"Sierra","email":"","affiliations":[{"id":36627,"text":"University of Colorado, Boulder","active":true,"usgs":false}],"preferred":false,"id":942954,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Giraldo-Silva, Ana","contributorId":357982,"corporation":false,"usgs":false,"family":"Giraldo-Silva","given":"Ana","affiliations":[{"id":85571,"text":"Public University of Navarre","active":true,"usgs":false}],"preferred":false,"id":942955,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Reed, Sasha C. 0000-0002-8597-8619","orcid":"https://orcid.org/0000-0002-8597-8619","contributorId":207498,"corporation":false,"usgs":true,"family":"Reed","given":"Sasha C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":942956,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70268278,"text":"70268278 - 2025 - Discovery of an intact Quaternary paleosol, Georgia Bight, USA","interactions":[],"lastModifiedDate":"2025-06-20T14:16:38.069571","indexId":"70268278","displayToPublicDate":"2025-06-18T09:08:35","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5841,"text":"Applied Sciences","onlineIssn":"2076-3417","active":true,"publicationSubtype":{"id":10}},"title":"Discovery of an intact Quaternary paleosol, Georgia Bight, USA","docAbstract":"<p><span>A previously buried paleosol was found on the continental shelf during a study of sea floor scour, nucleated by large artificial reef structures such as vessel hulks, barges, train cars, military vehicles, etc., called “scour nuclei”. It is a relic paleo-land surface of sapling-sized tree stumps, root systems, and fossil animal bone exhumed by scour processes active adjacent to the artificial reef structure. Over the span of five research cruises to the site in 2022–2024, soil samples were taken using hand excavation, PONAR grab samplers, split spoon, hollow tube auger, and a modified Shelby-style push box. High-definition (HD) video was taken using a Remotely Operated Vehicle (ROV) and diver-held cameras. Radiocarbon dating of wood samples returned ages of 42,015–43,417 calibrated years before present (cal yrBP). Pollen studies, together with the recovered macrobotanical remains, support our interpretation of the site as a freshwater forested wetland whose keystone tree species was&nbsp;</span><span class=\"html-italic\">Taxodium distichum</span><span>—bald cypress. The paleosol was identified as an Aquult, a sub-order of Ultisols where water tables are at or near the surface year-round. A deep (0.25 m+) argillic horizon comprised the bulk of the preserved soil. Comparable Ultisols found in Georgia wetlands include Typic Paleaquult (Grady and Bayboro series) soils.</span></p>","language":"English","publisher":"MDPI","doi":"10.3390/app15126859","usgsCitation":"Garrison, E., Newton, M., Prueitt, B., Jones, E., and Willard, D., 2025, Discovery of an intact Quaternary paleosol, Georgia Bight, USA: Applied Sciences, v. 15, 6859, 13 p., https://doi.org/10.3390/app15126859.","productDescription":"6859, 13 p.","ipdsId":"IP-177145","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":491444,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/app15126859","text":"Publisher Index Page"},{"id":491020,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Georgia","otherGeospatial":"Georgia Bight","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -80.6037065174064,\n              32.05700383452627\n            ],\n            [\n              -80.87744613056587,\n              32.073340398276045\n            ],\n            [\n              -81.16853543751718,\n              31.739498148416956\n            ],\n            [\n              -81.50026399128812,\n              31.09261341173041\n            ],\n            [\n              -81.51308221190993,\n              30.689275547735463\n            ],\n            [\n              -81.13422317222164,\n              30.688050731677237\n            ],\n            [\n              -80.6037065174064,\n              32.05700383452627\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"15","noUsgsAuthors":false,"publicationDate":"2025-06-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Garrison, Ervan G.","contributorId":357067,"corporation":false,"usgs":false,"family":"Garrison","given":"Ervan G.","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":940686,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Newton, Matthew","contributorId":357068,"corporation":false,"usgs":false,"family":"Newton","given":"Matthew","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":940687,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Prueitt, Benjamin","contributorId":357071,"corporation":false,"usgs":false,"family":"Prueitt","given":"Benjamin","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":940689,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jones, Emily C.","contributorId":357073,"corporation":false,"usgs":false,"family":"Jones","given":"Emily C.","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":940690,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Willard, Debra A. 0000-0003-4878-0942","orcid":"https://orcid.org/0000-0003-4878-0942","contributorId":269840,"corporation":false,"usgs":true,"family":"Willard","given":"Debra A.","affiliations":[],"preferred":true,"id":940693,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70268250,"text":"70268250 - 2025 - Mixed natal origins present management challenges for a non-native fish established throughout a modified river network","interactions":[],"lastModifiedDate":"2025-07-10T14:56:29.491021","indexId":"70268250","displayToPublicDate":"2025-06-18T08:25:04","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1169,"text":"Canadian Journal of Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Mixed natal origins present management challenges for a non-native fish established throughout a modified river network","docAbstract":"<p><span>Expansion of non-native brown trout (</span><i>Salmo trutta</i><span>) in the Colorado River below Glen Canyon Dam motivated reevaluation of suppression strategies to minimize potential impacts to native fishes in the Grand Canyon, Arizona, USA. Brown trout are one of several non-native fish species of management concern in this river reach, and understanding their natal sources and movement patterns may assist managers in planning suppression strategies. We identified trace elements in brown trout otoliths, which, when coupled with location-specific water chemistry data, identified brown trout natal origins over 19 years. Strontium and manganese concentrations revealed distinct emigration patterns from natal tributary streams and the mainstem Colorado River over two periods. Adult brown trout collected from throughout our study area showed mixed tributary and mainstem natal origins, which persisted during suppression efforts in a known spawning tributary. Unexpectedly, we found evidence of brown trout reproduction in the Colorado River for at least a decade before documentation through field monitoring. Our findings may inform but complicate the development of management strategies for system-wide brown trout suppression.</span></p>","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjfas-2024-0267","usgsCitation":"Akland, M., Limburg, K., Healy, B.D., and Pine, W.E., 2025, Mixed natal origins present management challenges for a non-native fish established throughout a modified river network: Canadian Journal of Fisheries and Aquatic Sciences, v. 82, p. 1-13, https://doi.org/10.1139/cjfas-2024-0267.","productDescription":"13 p.","startPage":"1","endPage":"13","ipdsId":"IP-168922","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":490920,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Colorado River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -111.63077077053144,\n              36.80786020404963\n            ],\n            [\n              -111.65750425155792,\n              36.81141589124036\n            ],\n            [\n              -111.76698028633918,\n              36.68345426369245\n            ],\n            [\n              -111.88230163058687,\n              36.503023995019646\n            ],\n            [\n              -111.84019781092644,\n              36.499299737249814\n            ],\n            [\n              -111.68048884893217,\n              36.68934775789845\n            ],\n            [\n              -111.63077077053144,\n              36.80786020404963\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"82","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Akland, Michael K.","contributorId":357023,"corporation":false,"usgs":false,"family":"Akland","given":"Michael K.","affiliations":[{"id":85311,"text":"Department of Environmental and Forest Biology, State University of New York College of Environmental Science and Forestry, Syracuse, New York, USA","active":true,"usgs":false}],"preferred":false,"id":940600,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Limburg, Karin E.","contributorId":356369,"corporation":false,"usgs":false,"family":"Limburg","given":"Karin E.","affiliations":[{"id":33387,"text":"SUNY-ESF","active":true,"usgs":false}],"preferred":false,"id":940601,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Healy, Brian D. 0000-0002-4402-638X","orcid":"https://orcid.org/0000-0002-4402-638X","contributorId":304257,"corporation":false,"usgs":true,"family":"Healy","given":"Brian","middleInitial":"D.","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":940602,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pine, William E. III","contributorId":139959,"corporation":false,"usgs":false,"family":"Pine","given":"William","suffix":"III","email":"","middleInitial":"E.","affiliations":[{"id":13332,"text":"Uni. of Florida Department of Wildlife Ecology and Conservation","active":true,"usgs":false}],"preferred":false,"id":940603,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70269667,"text":"70269667 - 2025 - Fine-scale spatial risk models to predict avian collisions with power lines","interactions":[],"lastModifiedDate":"2025-08-19T15:31:40.484785","indexId":"70269667","displayToPublicDate":"2025-06-18T08:12:42","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2163,"text":"Journal of Applied Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Fine-scale spatial risk models to predict avian collisions with power lines","docAbstract":"<p>1. Avian fatalities caused by collisions with overhead power lines are an important conservation issue worldwide. Although mitigation strategies can help reduce mortalities, given their considerable cost and the vast scale of power line infrastructure, cost-effective action requires that these efforts be prioritised to areas with the highest potential risk to birds. To date, this risk assessment has usually been guided by potentially biased information on the location of recorded fatalities. </p><p>2. Here we use five years of GPS tracking data from endangered Tasmanian wedge-tailed eagles to develop an alternative approach to risk assessment: fine-scale spatial risk models based on behavioural analyses. We built and cross-validated a model that generates spatially explicit predictions of the probability that eagles would cross power lines at hazardous altitudes throughout the entire Tasmanian electricity distribution network. </p><p>3. In our model, probability of power line crossings was most strongly associated with the proportion of forest edges, wet forest, open habitat, freshwater sources, and rural residential developments in the area surrounding the power lines. Cross-validation indicated that the model effectively predicted where Tasmanian wedge-tailed eagles cross power lines at low altitude. </p><p>4. Model validation suggested our approach was a powerful predictor of the locations of power line collisions involving eagles. The locations of almost all (94%) confirmed eagle fatalities were in the half of the total Tasmanian power line area assigned the higher risk by the model, and 50% of incidents occurred in the 30% of the power line area estimated to be highest risk. </p><p>5. <i>Synthesis and applications</i>. Our study illustrates a framework for using bird movement data to provide insights into avian behaviour and the risk they encounter around power line infrastructure. Electricity delivery industries can use these models to identify the electrical infrastructure that poses the highest risk to avian survival and prioritise mitigation efforts, thereby optimizing the benefit of investments to reduce detrimental effects on biodiversity. Our model can direct pre-emptive mitigation across Tasmania’s 20,310 km of distribution infrastructure to meet management targets aiming to reduce the negative effects of power lines on the Tasmanian wedge-tailed eagle.</p>","language":"English","publisher":"British Ecological Society","doi":"10.1111/1365-2664.70076","usgsCitation":"Pay, J.M., Cameron, E.Z., Hawkins, C.E., Johnson, C., Koch, A.J., Wiersma, J., and Katzner, T., 2025, Fine-scale spatial risk models to predict avian collisions with power lines: Journal of Applied Ecology, v. 62, no. 8, p. 1820-1830, https://doi.org/10.1111/1365-2664.70076.","productDescription":"11 p.","startPage":"1820","endPage":"1830","ipdsId":"IP-163294","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":493113,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":493326,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1365-2664.70076","text":"Publisher Index Page"}],"country":"Australia","otherGeospatial":"Tasmania","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              143.86088831282336,\n              -40.405798345451885\n            ],\n            [\n              143.86088831282336,\n              -44.063653865697944\n            ],\n            [\n              149.28385412411444,\n              -44.063653865697944\n            ],\n            [\n              149.28385412411444,\n              -40.405798345451885\n            ],\n            [\n              143.86088831282336,\n              -40.405798345451885\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"62","issue":"8","noUsgsAuthors":false,"publicationDate":"2025-06-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Pay, James M.","contributorId":245078,"corporation":false,"usgs":false,"family":"Pay","given":"James","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":944335,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cameron, Elissa Z.","contributorId":245084,"corporation":false,"usgs":false,"family":"Cameron","given":"Elissa","email":"","middleInitial":"Z.","affiliations":[],"preferred":false,"id":944336,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hawkins, Clare E.","contributorId":245079,"corporation":false,"usgs":false,"family":"Hawkins","given":"Clare","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":944337,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Johnson, Christopher","contributorId":334072,"corporation":false,"usgs":false,"family":"Johnson","given":"Christopher","affiliations":[{"id":36942,"text":"University of California, Berkeley","active":true,"usgs":false}],"preferred":false,"id":944338,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Koch, Amelia J.","contributorId":245080,"corporation":false,"usgs":false,"family":"Koch","given":"Amelia","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":944339,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wiersma, Jason M.","contributorId":358878,"corporation":false,"usgs":false,"family":"Wiersma","given":"Jason M.","affiliations":[{"id":85698,"text":"Forest Practices Authority, 30 Patrick St, Hobart, TAS, AustraliaForest Practices Authority, 30 Patrick St, Hobart, TAS, Australia","active":true,"usgs":false}],"preferred":false,"id":944340,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Katzner, Todd E. 0000-0003-4503-8435 tkatzner@usgs.gov","orcid":"https://orcid.org/0000-0003-4503-8435","contributorId":191353,"corporation":false,"usgs":true,"family":"Katzner","given":"Todd E.","email":"tkatzner@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":944341,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70274278,"text":"70274278 - 2025 - Considerations for using tag-returns to monitor targeted removal of invasive fishes","interactions":[],"lastModifiedDate":"2026-03-24T16:46:08.980961","indexId":"70274278","displayToPublicDate":"2025-06-18T00:00:00","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"title":"Considerations for using tag-returns to monitor targeted removal of invasive fishes","docAbstract":"<p>Objective</p><p><span>Targeted removals are used for management of some invasive fish populations. Tag–return studies are one approach that can be used to assess the efficacy of targeted removals. However, there are many decisions to make when designing a tag–return study. We used simulation modeling to outline general guidelines for consideration when designing efficient tag–return studies to measure annual removal rates of invasive fish, particularly invasive carps.</span></p><p><span>Methods</span></p><p><span>We simulated data sets using scenarios with varying numbers of fish tagged per year, removal rates, tag reporting rates, tag retention rates, and study durations. We generated the data sets under a set of “known” parameters with added stochasticity; we then fitted the simulated data sets to a Bayesian tag–return model and measured the precision and accuracy of the model-estimated removal rates.</span></p><p><span>Results</span></p><p><span>We found that the model was able to predict removal rates without bias for most of the scenarios. However, we did find patterns in the precision of the predictions that could help to inform tag–return studies. When the proportion of the population removed through harvest was constant, the proportion of the population removed per year and the probability that harvested tags were reported had the largest effect on precision. The number of tags released per year and the study duration also had moderate effects. For scenarios testing the ability of the model to predict removal rates in stochastic populations, the precision of the model was primarily influenced by the number of fish tagged, the underlying nature of the stochasticity, and whether fish were tagged during the year of the prediction.</span></p><p><span>Conclusions</span></p><p><span>Based on our simulations, we outline how study objectives, the underlying population variability, and the tolerance range for error can guide decisions regarding the number of fish to tag, how to monitor tag return rates, and how long to conduct a study.</span></p>","language":"English","publisher":"American Fisheries Society","doi":"10.1093/najfmt/vqaf049","usgsCitation":"Stanton, J.C., Marcek, B.J., and Brey, M.K., 2025, Considerations for using tag-returns to monitor targeted removal of invasive fishes: North American Journal of Fisheries Management, v. 45, no. 4, p. 669-683, https://doi.org/10.1093/najfmt/vqaf049.","productDescription":"15 p.","startPage":"669","endPage":"683","ipdsId":"IP-164064","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":501964,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P13DJCBK","text":"USGS data release","linkHelpText":"Code release for simulated tag-return study for monitoring invasive fish removals"},{"id":501681,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/najfmt/vqaf049","text":"Publisher Index Page"},{"id":501474,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"45","issue":"4","noUsgsAuthors":false,"publicationDate":"2025-06-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Stanton, Jessica C. 0000-0002-6225-3703 jcstanton@usgs.gov","orcid":"https://orcid.org/0000-0002-6225-3703","contributorId":5634,"corporation":false,"usgs":true,"family":"Stanton","given":"Jessica","email":"jcstanton@usgs.gov","middleInitial":"C.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":957555,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Marcek, Benjamin J.","contributorId":367732,"corporation":false,"usgs":false,"family":"Marcek","given":"Benjamin","middleInitial":"J.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":957556,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brey, Marybeth K. 0000-0003-4403-9655 mbrey@usgs.gov","orcid":"https://orcid.org/0000-0003-4403-9655","contributorId":187651,"corporation":false,"usgs":true,"family":"Brey","given":"Marybeth","email":"mbrey@usgs.gov","middleInitial":"K.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":957557,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70268060,"text":"sir20255051 - 2025 - Estimated hydrogeologic, spatial, and temporal distribution of self-supplied domestic groundwater withdrawals for aquifers of the Virginia Coastal Plain","interactions":[],"lastModifiedDate":"2025-08-14T19:36:34.867035","indexId":"sir20255051","displayToPublicDate":"2025-06-17T10:40:00","publicationYear":"2025","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":"2025-5051","displayTitle":"Estimated Hydrogeologic, Spatial, and Temporal Distribution of Self-Supplied Domestic Groundwater Withdrawals for Aquifers of the Virginia Coastal Plain","title":"Estimated hydrogeologic, spatial, and temporal distribution of self-supplied domestic groundwater withdrawals for aquifers of the Virginia Coastal Plain","docAbstract":"<p>Water use from private-domestic wells accounts for nearly 40 percent of total groundwater withdrawals in the Virginia Coastal Plain Physiographic Province (henceforth called the Virginia Coastal Plain). However, because self-supplied domestic water use generally falls below the Virginia Department of Environmental Quality (VDEQ) reporting and management threshold of 300,000 gallons per month, quantifying these withdrawals is challenging. This report builds upon the foundation of previous U.S. Geological Survey investigations by providing revised techniques to improve estimates of the aquifer source, spatial distribution, and monthly magnitude of these groundwater withdrawals.</p><p>The aquifer sources of private-domestic wells in the Virginia Coastal Plain were estimated by cross-referencing 8,264 well records from the VDEQ and the Virginia Department of Health to a digital model of the Virginia Coastal Plain hydrogeologic framework. This analysis highlights the regional importance of the Yorktown-Eastover, Potomac, and surficial aquifers. Collectively, these three aquifers account for 80 percent of self-supplied domestic groundwater withdrawals.</p><p>The population using self-supplied domestic water was estimated using census blocks, well-use ratios, building footprints, and land-use and land-cover data to produce a high-resolution, disaggregated, raster-based dataset. This approach improves upon previous models at the census-block or road-network scale by reducing the low-density spread of the self-supplied domestic population across undeveloped areas and concentrating the population and its corresponding water use in the areas where it is most likely to occur. Results show that an estimated 475,332 people comprise the 2020 self-supplied domestic population of the Virginia Coastal Plain, an increase of 5.7 percent since 2010, and the greatest concentrations of self-supplied domestic population surround large cities. Estimates could be further refined with the addition of current and complete spatial data on public water-system service areas.</p><p>The quantity of water used by the self-supplied domestic population was estimated by modifying published state per-capita water-use coefficients with the corresponding monthly variability assessed from Virginia Coastal Plain public water-system withdrawal data. This analysis estimates an average increase of 12 percent from June through August and an average decrease of 8 percent from December through March from the baseline annual average of 80 gallons per day per capita, which generally matches similar studies in the eastern United States.</p><p>The application of these revised methodologies for the estimation of private-domestic wells and the self-supplied domestic population improves understanding of domestic groundwater use in the Virginia Coastal Plain across hydrogeologic, spatial, and temporal scales. These revisions help better inform water-resource managers and decision makers and support higher resolution groundwater modeling. Furthermore, these methods are transferrable to other areas where self-supplied domestic water withdrawals are important to the overall water budget.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20255051","isbn":"978-1-4113-4609-3","collaboration":"Prepared in cooperation with Virginia Department of Environmental Quality","usgsCitation":"Kearns, M.R., and Pope, J.P., 2025, Estimated hydrogeologic, spatial, and temporal distribution of self-supplied domestic groundwater withdrawals for aquifers of the Virginia Coastal Plain: U.S. Geological Survey Scientific Investigations Report 2025–5051, 45 p., https://doi.org/10.3133/sir20255051.","productDescription":"Report: vii, 45 p.; Data release","numberOfPages":"45","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-168850","costCenters":[{"id":37280,"text":"Virginia and West Virginia Water Science Center ","active":true,"usgs":true}],"links":[{"id":494146,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118651.htm","linkFileType":{"id":5,"text":"html"}},{"id":490433,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P1QJQ2CB","text":"USGS data release","linkHelpText":"Estimated aquifer distribution for private domestic wells; estimated spatial distribution of the self-supplied domestic population for 2020 and 2010; and estimated monthly domestic self-supplied withdrawals of groundwater for the Virginia Coastal Plain"},{"id":490432,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2025/5051/images/"},{"id":490431,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2025/5051/sir20255051.XML","linkFileType":{"id":8,"text":"xml"},"description":"SIR 2025-5051 XML"},{"id":490428,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2025/5051/coverthb.jpg"},{"id":490429,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2025/5051/sir20255051.pdf","text":"Report","size":"13.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2025-5051 PDF"},{"id":490430,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20255051/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2025-5051 HTML"}],"country":"United States","state":"Virginia","otherGeospatial":"Virginia Coastal Plain","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -76.32710341724686,\n              36.556784944765795\n            ],\n            [\n              -75.86947557927473,\n              36.55265452745853\n            ],\n            [\n              -75.8900431225546,\n              37.161549677245205\n            ],\n            [\n              -75.32957756818404,\n              38.02121666772172\n            ],\n            [\n              -76.21912381502888,\n              37.907709637048185\n            ],\n            [\n              -76.67160976718064,\n              38.146680392024706\n            ],\n            [\n              -77.04182554621384,\n              38.31631983320398\n            ],\n            [\n              -77.04182554621384,\n              38.40904986490523\n            ],\n            [\n              -77.23721720737078,\n              38.34052172806261\n            ],\n            [\n              -77.30406172302983,\n              38.39293143681613\n            ],\n            [\n              -77.18579834917193,\n              38.64236292442064\n            ],\n            [\n              -77.00583234547452,\n              38.722640223692224\n            ],\n            [\n              -77.03717799709146,\n              38.83873960192227\n            ],\n            [\n              -77.1282913174048,\n              38.95928536652022\n            ],\n            [\n              -77.23580503537455,\n              38.99328476178536\n            ],\n            [\n              -77.29958450463103,\n              39.054158449342225\n            ],\n            [\n              -77.6385260561967,\n              39.00744529354114\n            ],\n            [\n              -77.6421696520891,\n              38.07245238381515\n            ],\n            [\n              -77.5875012530419,\n              36.77147021603372\n            ],\n            [\n              -77.58567879299983,\n              36.54488432804379\n            ],\n            [\n              -76.32710341724686,\n              36.556784944765795\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","contact":"<p>Director, <a href=\"https://www.usgs.gov/centers/virginia-and-west-virginia-water-science-center\" data-mce-href=\"https://www.usgs.gov/centers/virginia-and-west-virginia-water-science-center\">Virginia and West Virginia Water Science Center</a><br>U.S. Geological Survey<br>1730 East Parham Road<br>Richmond, Virginia 23228</p><p><a href=\"../contact\" data-mce-href=\"../contact\">Contact Pubs Warehouse</a></p>","tableOfContents":"<ul><li>1. Introduction</li><li>2. Distribution of Private-Domestic Wells Among Virginia Coastal Plain Aquifers</li><li>3. Spatial Distribution of Self-Supplied Domestic Population Across the Virginia Coastal Plain</li><li>4. Temporal Distribution of Self-Supplied Domestic Withdrawals in the Virginia Coastal Plain</li><li>5. Estimated Self-Supplied Domestic Water Withdrawal in the Virginia Coastal Plain</li><li>6. Summary</li></ul>","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"publishedDate":"2025-06-17","noUsgsAuthors":false,"publicationDate":"2025-06-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Kearns, Matthew R. 0000-0002-7338-5146","orcid":"https://orcid.org/0000-0002-7338-5146","contributorId":288957,"corporation":false,"usgs":true,"family":"Kearns","given":"Matthew","email":"","middleInitial":"R.","affiliations":[{"id":37280,"text":"Virginia and West Virginia Water Science Center ","active":true,"usgs":true}],"preferred":true,"id":940077,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pope, Jason P. 0000-0003-3199-993X jpope@usgs.gov","orcid":"https://orcid.org/0000-0003-3199-993X","contributorId":2044,"corporation":false,"usgs":true,"family":"Pope","given":"Jason","email":"jpope@usgs.gov","middleInitial":"P.","affiliations":[{"id":614,"text":"Virginia Water Science Center","active":true,"usgs":true},{"id":37759,"text":"VA/WV Water Science Center","active":true,"usgs":true}],"preferred":true,"id":940078,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70270412,"text":"70270412 - 2025 - Modeling daily ice cover in northern hemisphere lakes with a long short‐term memory neural network","interactions":[],"lastModifiedDate":"2025-08-19T15:16:54.496662","indexId":"70270412","displayToPublicDate":"2025-06-17T10:15:13","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Modeling daily ice cover in northern hemisphere lakes with a long short‐term memory neural network","docAbstract":"<p><span>Quantifying lake ice loss is crucial for understanding the impact of climate change on lake ecosystems. In this study, we trained a deep learning model (Long-Short Term Memory with Landsat observations, 1984–2012) to simulate Northern Hemisphere lake ice changes at a fine spatial scale (&gt; 0.1 km<sup>2</sup>) </span><span>from 1980 to 2022. The model achieved good performance overall during the test period (2013–2022), and the derived ice-on and ice-off matched well with two independent ice phenology data sets. Results reveal a 76.8% increase in intermittently ice-covered lakes from the 1980s to the 2010s, alongside a 10.7-day shorter ice duration and a 3.9 percentage-points reduction in annual mean ice cover fractions. The model can track daily partial ice cover changes, providing a novel contribution to understanding shifts in lake ice cover with climate change. These findings can provide valuable insights for future limnology studies, such as improving estimates of greenhouse gas emissions from lakes.</span></p>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2024gl113544","usgsCitation":"He, X., Andreadis, K.M., Roy, A.H., Langhorst, T., Kumar, A., and Butler, C.S., 2025, Modeling daily ice cover in northern hemisphere lakes with a long short‐term memory neural network: Geophysical Research Letters, v. 52, no. 12, e2024GL113544,10 p., https://doi.org/10.1029/2024gl113544.","productDescription":"e2024GL113544,10 p.","ipdsId":"IP-165442","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":494970,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P13ZGUGE","text":"USGS data release","linkHelpText":"A Long Short Term Memory model for predicting daily lake ice cover changes in the Northern Hemisphere"},{"id":494456,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2024gl113544","text":"Publisher Index Page"},{"id":494313,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"52","issue":"12","noUsgsAuthors":false,"publicationDate":"2025-06-17","publicationStatus":"PW","contributors":{"authors":[{"text":"He, Xinchen","contributorId":316775,"corporation":false,"usgs":false,"family":"He","given":"Xinchen","affiliations":[{"id":36396,"text":"University of Massachusetts","active":true,"usgs":false}],"preferred":false,"id":946355,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Andreadis, Konstantinos M.","contributorId":359867,"corporation":false,"usgs":false,"family":"Andreadis","given":"Konstantinos","middleInitial":"M.","affiliations":[{"id":36396,"text":"University of Massachusetts","active":true,"usgs":false}],"preferred":false,"id":946356,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Roy, Allison H. 0000-0002-8080-2729 aroy@usgs.gov","orcid":"https://orcid.org/0000-0002-8080-2729","contributorId":4240,"corporation":false,"usgs":true,"family":"Roy","given":"Allison","email":"aroy@usgs.gov","middleInitial":"H.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":946357,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Langhorst, Theodore","contributorId":292528,"corporation":false,"usgs":false,"family":"Langhorst","given":"Theodore","email":"","affiliations":[{"id":27517,"text":"University of North Carolina - Chapel Hill","active":true,"usgs":false}],"preferred":false,"id":946358,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kumar, Abhishek","contributorId":316778,"corporation":false,"usgs":false,"family":"Kumar","given":"Abhishek","affiliations":[{"id":36396,"text":"University of Massachusetts","active":true,"usgs":false}],"preferred":false,"id":946359,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Butler, Caitlyn S.","contributorId":359869,"corporation":false,"usgs":false,"family":"Butler","given":"Caitlyn","middleInitial":"S.","affiliations":[{"id":36396,"text":"University of Massachusetts","active":true,"usgs":false}],"preferred":false,"id":946360,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70268839,"text":"70268839 - 2025 - The impact of burial diagenesis on soil-formed minerals in paleosols using stable isotopes of phyllosilicates and carbonate clumped isotopes","interactions":[],"lastModifiedDate":"2025-07-08T17:13:17.514089","indexId":"70268839","displayToPublicDate":"2025-06-17T10:09:10","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1213,"text":"Chemical Geology","active":true,"publicationSubtype":{"id":10}},"title":"The impact of burial diagenesis on soil-formed minerals in paleosols using stable isotopes of phyllosilicates and carbonate clumped isotopes","docAbstract":"<p><span>To understand the effects of burial diagenesis on the stable isotope geochemistry of soil-formed clay and carbonate minerals in paleosols, samples were collected from seven cores, spanning middle- to upper-Pennsylvanian strata of the Illinois Basin, with varied maximum burial depths of 1–3&nbsp;km. Mixed-layer illite-smectite and kaolinite mixtures give δ</span><sup>2</sup><span>H and δ</span><sup>18</sup><span>O values of −83&nbsp;‰ to −36&nbsp;‰ and 11.9&nbsp;‰ to 21.1&nbsp;‰ (VSMOW), respectively. After carbonates were screened petrographically for diagenetic textures using transmitted light and cathodoluminescence, measured clumped isotope Δ</span><sub>47</sub><span>&nbsp;values range from 0.504 to 0.563&nbsp;‰ (I-CDES). Resulting mineral formation temperatures for phyllosilicate mineral mixtures are 28 to 66&nbsp;°C (mean&nbsp;=&nbsp;47&nbsp;°C), whereas T(Δ</span><sub>47</sub><span>) estimates for calcites are 36 to 61&nbsp;°C (mean&nbsp;=&nbsp;45&nbsp;°C). Calculated δ</span><sup>18</sup><span>O</span><sub>water</sub><span>&nbsp;values from which phyllosilicate minerals and calcites precipitated under isotopic equilibrium ranges from −7.1 to −1.2 ‰ and&nbsp;−&nbsp;1.4 to +4.9 ‰, respectively. Closed and open-system phyllosilicate-fluid exchange modeling indicates that phyllosilicate alteration occurred in the presence of a low temperature brine or meteoric water and is interpreted to occur in a layer-by-layer illitization transformation. Due to the lack of diagenetic textures and positively correlated T(Δ</span><sub>47</sub><span>) and δ</span><sup>18</sup><span>O</span><sub>water</sub><span>, calcites are interpreted to have undergone solid-state bond reordering. Despite low to moderate temperatures (&lt;125&nbsp;°C) and varying depths of shallow burial (1–3&nbsp;km), solid-state transformation of phyllosilicates and calcites indicates paleosols had prolonged exposure to burial conditions which has implications for the use of paleosol minerals for paleoenvironmental reconstructions.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.chemgeo.2025.122941","usgsCitation":"McIntosh, J.A., Tabor, N., and Montañez, I., 2025, The impact of burial diagenesis on soil-formed minerals in paleosols using stable isotopes of phyllosilicates and carbonate clumped isotopes: Chemical Geology, v. 692, 122941, 17 p., https://doi.org/10.1016/j.chemgeo.2025.122941.","productDescription":"122941, 17 p.","ipdsId":"IP-171865","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":492072,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.chemgeo.2025.122941","text":"Publisher Index Page"},{"id":491834,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Illinois, Indiana, Kentucky","otherGeospatial":"Illinois Basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -90.26016848796888,\n              41.70274182675729\n            ],\n            [\n              -90.26016848796888,\n              36.61086981521096\n            ],\n            [\n              -86.39382164848195,\n              36.61086981521096\n            ],\n            [\n              -86.39382164848195,\n              41.70274182675729\n            ],\n            [\n              -90.26016848796888,\n              41.70274182675729\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"692","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"McIntosh, Julia A. 0000-0003-2819-8664","orcid":"https://orcid.org/0000-0003-2819-8664","contributorId":331662,"corporation":false,"usgs":true,"family":"McIntosh","given":"Julia","email":"","middleInitial":"A.","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":942314,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tabor, Neil J. 0000-0001-8582-9886","orcid":"https://orcid.org/0000-0001-8582-9886","contributorId":357718,"corporation":false,"usgs":false,"family":"Tabor","given":"Neil J.","affiliations":[{"id":20300,"text":"Southern Methodist University","active":true,"usgs":false}],"preferred":false,"id":942315,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Montañez, Isabel P. 0000-0003-0492-3796","orcid":"https://orcid.org/0000-0003-0492-3796","contributorId":357719,"corporation":false,"usgs":false,"family":"Montañez","given":"Isabel P.","affiliations":[{"id":17619,"text":"University of California at Davis","active":true,"usgs":false}],"preferred":false,"id":942316,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70268299,"text":"70268299 - 2025 - Are equilibrium shoreline models just convolutions?","interactions":[],"lastModifiedDate":"2025-06-20T14:52:37.1233","indexId":"70268299","displayToPublicDate":"2025-06-17T09:48:47","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7357,"text":"JGR Earth Surface","active":true,"publicationSubtype":{"id":10}},"title":"Are equilibrium shoreline models just convolutions?","docAbstract":"<p><span>Yes. Equilibrium shoreline models, which simulate wave-driven cross-shore erosion and accretion, are mathematically equivalent to a discrete convolution (i.e., a weighted, moving average) of a time series of wave-forcing conditions with a parameterized memory-decay kernel function. The direct equivalence between equilibrium shoreline models and convolutions reveals key theoretical aspects of equilibrium behavior. Convolutions (representing quasi-low-pass filter operations) provide an intuitive theoretical description of shoreline erosion and accretion behavior in response to waves: that is, shoreline position often mirrors the weighted moving average of wave time series. Model-convolution equivalence also provides a conceptual basis to interpret, evaluate, and construct data-driven Machine-Learning/Deep-Learning (ML/DL) models that use convolutions to extract features from data and then apply them for prediction (e.g., Convolutional Neural Networks (CNNs)). Finally, our findings provide a methodological pathway (based on Fourier transforms) for future understanding of wave-driven shoreline change, which can be used to interpret the coherence between the frequency spectrum of the processes of waves and shoreline change and construct more computationally efficient and effective shoreline-modeling approaches.</span></p>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2025JF008452","usgsCitation":"Vitousek, S., Buscombe, D.D., Gomez-de la Peña, E., Calcraft, K., Lundine, M.A., Splinter, K., Giovanni Coco, and Barnard, P.L., 2025, Are equilibrium shoreline models just convolutions?: JGR Earth Surface, v. 130, no. 6, e2025JF008452, 30 p., https://doi.org/10.1029/2025JF008452.","productDescription":"e2025JF008452, 30 p.","ipdsId":"IP-172699","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":491493,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2025jf008452","text":"Publisher Index Page"},{"id":491025,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"130","issue":"6","noUsgsAuthors":false,"publicationDate":"2025-06-17","publicationStatus":"PW","contributors":{"authors":[{"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":940730,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Buscombe, Daniel D. 0000-0001-6217-5584","orcid":"https://orcid.org/0000-0001-6217-5584","contributorId":198817,"corporation":false,"usgs":false,"family":"Buscombe","given":"Daniel","middleInitial":"D.","affiliations":[],"preferred":false,"id":940731,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gomez-de la Peña, Eduardo","contributorId":357091,"corporation":false,"usgs":false,"family":"Gomez-de la Peña","given":"Eduardo","affiliations":[{"id":38833,"text":"University of Auckland","active":true,"usgs":false}],"preferred":false,"id":940732,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Calcraft, Kit","contributorId":357094,"corporation":false,"usgs":false,"family":"Calcraft","given":"Kit","affiliations":[{"id":65517,"text":"University of New South Wales - Sydney","active":true,"usgs":false}],"preferred":false,"id":940733,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lundine, Mark A. 0000-0002-2878-1713","orcid":"https://orcid.org/0000-0002-2878-1713","contributorId":339934,"corporation":false,"usgs":true,"family":"Lundine","given":"Mark","middleInitial":"A.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":940734,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Splinter, Kristen D.","contributorId":357097,"corporation":false,"usgs":false,"family":"Splinter","given":"Kristen D.","affiliations":[{"id":65517,"text":"University of New South Wales - Sydney","active":true,"usgs":false}],"preferred":false,"id":940735,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Giovanni Coco","contributorId":357100,"corporation":false,"usgs":false,"family":"Giovanni Coco","affiliations":[{"id":38833,"text":"University of Auckland","active":true,"usgs":false}],"preferred":false,"id":940736,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Barnard, Patrick L. 0000-0003-1414-6476 pbarnard@usgs.gov","orcid":"https://orcid.org/0000-0003-1414-6476","contributorId":140982,"corporation":false,"usgs":true,"family":"Barnard","given":"Patrick","email":"pbarnard@usgs.gov","middleInitial":"L.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":940737,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70266861,"text":"sir20245061 - 2025 - Estimating daily public supply water use by drinking water service area in New Jersey","interactions":[],"lastModifiedDate":"2025-06-17T13:40:29.748047","indexId":"sir20245061","displayToPublicDate":"2025-06-17T09:05:00","publicationYear":"2025","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":"2024-5061","displayTitle":"Estimating Daily Public Supply Water Use by Drinking Water Service Area in New Jersey","title":"Estimating daily public supply water use by drinking water service area in New Jersey","docAbstract":"<p>This report, prepared in cooperation with the New Jersey Department of Environmental Protection, presents a method for estimating daily public supply water use by drinking water service area systems for New Jersey. The ability to accurately estimate daily public supply water use could help water supply planners in New Jersey better understand and manage the state’s limited water resources and balance the competing needs for freshwater resources. Data sources for this work include daily public supply water-use data from 2016 through 2020 acquired from New Jersey American Water for 15 drinking water service areas and monthly data exported from the New Jersey Department of Environmental Protection’s online water transfer data model database (known as NJWaTr). The two datasets were compared by aggregating the daily data to a monthly timescale. Statistical regression analysis was applied to the daily data, along with climate data, to evaluate what factors are influential in estimating daily fluctuations and trends in daily public supply water use. Fifteen regression equations were developed, one for each of the 15 drinking water service area systems for which daily data were acquired. Regression equations for systems that had seasonal patterns performed better than equations for non-seasonal systems. For the test year (2020), the average adjusted coefficient of determination for the linear regression with autoregressive errors model among systems with seasonality was 0.78; the average adjusted coefficient of determination for the linear regression with autoregressive errors model among systems with little or no seasonality was 0.25. The effects of anomalous data in the regression analysis were examined by comparing adjusted coefficient of determination values when the atypical data points were removed versus when they were retained in the analysis. Overall, including the anomalous data did not have a large effect on the results, and thus the data were retained for this study.&nbsp;</p><p>In addition to developing regression equations, all 589 unique drinking water service area systems in New Jersey were characterized based on socio-economic data and monthly water-use data from NJWaTr. Systems that are located near the New Jersey coast, serve populations larger than 1,970 people, or serve areas that have median property values over $256,250 tended to demonstrate seasonal water-use behaviors. Systems that have mostly urban residential land use tended to show little to no seasonal water-use behaviors. Finally, a method was developed to disaggregate monthly data to a daily timescale and was tested against systems for which daily data were not available. Two regression equation forms were developed to be applied to systems beyond the 15 systems from which the original equations were developed; one equation was developed for use when all drinking water service area systems showed little to no seasonality, and the other equation was developed for use when systems displayed seasonal behavior.&nbsp;</p><p>To the extent possible, uncertainty and possible sources of error were identified and examined in relation to the regression model equations developed. Additional daily data from these 15 systems (over different years) and daily data from different systems could be used to further evaluate the results of the disaggregation through a comprehensive assessment of error. Further adjustments to the regression equations could be made, ultimately enhancing their accuracy.&nbsp;</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20245061","collaboration":"Prepared in cooperation with New Jersey Department of Environmental Protection","programNote":"Water Availability and Use Science Program","usgsCitation":"Shourds, J.L., and Scott, M.H., 2025, Estimating daily public supply water use by drinking water service area in New Jersey: U.S. Geological Survey Scientific Investigations Report 2024–5061, 90 p., https://doi.org/10.3133/sir20245061.","productDescription":"Report: xi, 90 p.; Appendix","numberOfPages":"90","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-151668","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":485928,"rank":4,"type":{"id":31,"text":"Publication 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Jersey\",\"nation\":\"USA  \"}}]}","contact":"<p><a href=\"mailto:dc_nj@usgs.gov\" data-mce-href=\"mailto:dc_nj@usgs.gov\">Director</a>, <a href=\"https://www.usgs.gov/centers/new-jersey-water-science-center\" data-mce-href=\"https://www.usgs.gov/centers/new-jersey-water-science-center\">New Jersey Water Science Center</a><br>U.S. Geological Survey<br>3450 Princeton Pike<br>Suite 110<br>Lawrenceville, NJ 08648</p>","tableOfContents":"<ul><li>Preface</li><li>Acknowledgements</li><li>Abstract</li><li>Introduction</li><li>Purpose and Scope</li><li>Public Supply Water-Use Data in New Jersey</li><li>Drinking Water Service Area System Characterizations</li><li>Development of a Daily Water-Use Regression Model</li><li>Disaggregation of Monthly-to-Daily Water-Use Estimates</li><li>Summary</li><li>References Cited</li><li>Appendix 1. Drinking water service area systems characteristics for all 589 unique systems in New Jersey</li></ul>","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"publishedDate":"2025-06-17","noUsgsAuthors":false,"publicationDate":"2025-06-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Shourds, Jennifer L. 0000-0002-7631-9734 jshourds@usgs.gov","orcid":"https://orcid.org/0000-0002-7631-9734","contributorId":5821,"corporation":false,"usgs":true,"family":"Shourds","given":"Jennifer","email":"jshourds@usgs.gov","middleInitial":"L.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":936965,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Scott, Malia H. 0000-0002-1393-1512","orcid":"https://orcid.org/0000-0002-1393-1512","contributorId":350909,"corporation":false,"usgs":true,"family":"Scott","given":"Malia H.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":936966,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70267978,"text":"70267978 - 2025 - The stratigraphic record of the mid-Piacenzian warm period on the Atlantic Coastal Plain","interactions":[],"lastModifiedDate":"2025-09-09T16:04:07.775087","indexId":"70267978","displayToPublicDate":"2025-06-16T10:58:45","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3481,"text":"Stratigraphy","active":true,"publicationSubtype":{"id":10}},"title":"The stratigraphic record of the mid-Piacenzian warm period on the Atlantic Coastal Plain","docAbstract":"<p><span>Anthropogenic climate change is an existential threat to our planet, impacting everything from the delicate balance of ecosystems to the availability of vital resources. Coastal regions, particularly vulnerable to the impacts of climate change due to rising sea levels and changing weather patterns, are experiencing increased erosion, flooding, and habitat loss. Understanding how coastal regions responded to past warming is crucial for developing effective adaptation and mitigation strategies. One past interval commonly used to examine and compare with climate model projections of near future conditions is the mid-Piacenzian Warm Period (MPWP) which occurred between*3.3 and 3.0 Ma. Here we review the stratigraphy of Atlantic Coastal Plain (ACP) sediments to determine the stratigraphic position of the MPWP by evaluating ages based upon existing and new planktic foraminifer occurrence data calibrated to the current geologic time scale (GTS2020). We identify geologic formations representing pre-, syn-, and post-MPWP environments. The Sunken Meadow Member of the Yorktown Formation in Virginia and North Carolina and the Wabasso beds in the subsurface of Georgia and Florida both fall within Planktic Foraminiferal Zone PL1 and represent pre-MPWP Pliocene deposits. Parts of the Yorktown Formation in southeastern Virginia and northern North Carolina, the Duplin Formation in North Carolina and South Carolina, and the Raysor Formation in South Carolina and Georgia, fall within Planktic Foraminiferal Zone PL3 and were deposited following a major regression associated with a global drop in sea level during Marine Isotope Stage (MIS) M2 and represent syn-MPWP deposits. Representing the immediately post-MPWP climate conditions (Planktic Foraminiferal Zone PL5) are the Chowan River, Bear Bluff, and Cypresshead Formations. This work provides a record of the MPWP from Georgia to Virginia and provides a stratigraphic framework within which the impacts of a profound global warming on the east coast of the United States can be assessed.</span></p>","language":"English","publisher":"Micropaleontological Press","doi":"10.47894/stra.22.2.00","usgsCitation":"Dowsett, H., and Spivey, W., 2025, The stratigraphic record of the mid-Piacenzian warm period on the Atlantic Coastal Plain: Stratigraphy, v. 22, no. 2, p. 81-97, https://doi.org/10.47894/stra.22.2.00.","productDescription":"17 p.","startPage":"81","endPage":"97","ipdsId":"IP-167251","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":490297,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.micropress.org/microaccess/stratigraphy/issue-412/article-2424","linkFileType":{"id":5,"text":"html"}},{"id":495251,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Georgia, North Carolina, South Carolina, Virginia","otherGeospatial":"Atlantic Coastal Plain","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -75.2540064137628,\n              37.9661310516864\n            ],\n            [\n              -77.45393664738447,\n              37.57788480662157\n            ],\n            [\n              -82.81553889394615,\n              31.49173122752032\n            ],\n            [\n              -82.4849451212944,\n              30.69984073209814\n            ],\n            [\n              -81.58807068387608,\n              30.841401404258605\n            ],\n            [\n              -78.7009680731669,\n              33.43137207763918\n            ],\n            [\n              -75.88995103042635,\n              34.91166522689612\n            ],\n            [\n              -75.2540064137628,\n              37.9661310516864\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"22","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Dowsett, Harry J. 0000-0003-1983-7524","orcid":"https://orcid.org/0000-0003-1983-7524","contributorId":316789,"corporation":false,"usgs":true,"family":"Dowsett","given":"Harry J.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":939852,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Spivey, Whittney 0000-0003-1111-3361 wspivey@usgs.gov","orcid":"https://orcid.org/0000-0003-1111-3361","contributorId":214849,"corporation":false,"usgs":true,"family":"Spivey","given":"Whittney","email":"wspivey@usgs.gov","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":939853,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70268362,"text":"70268362 - 2025 - Characterizing water-quality response after the 2020 Cameron Peak Fire using a novel application of the Weighted Regressions on Time, Discharge, and Season method","interactions":[],"lastModifiedDate":"2025-06-24T14:08:12.18671","indexId":"70268362","displayToPublicDate":"2025-06-16T09:02:43","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1924,"text":"Hydrological Processes","active":true,"publicationSubtype":{"id":10}},"title":"Characterizing water-quality response after the 2020 Cameron Peak Fire using a novel application of the Weighted Regressions on Time, Discharge, and Season method","docAbstract":"<p><span>The frequency and severity of wildfire activity in the western United States emphasises the utility of hydrologic models to predict water-quality response. This study presents a novel application of the Weighted Regressions on Time, Discharge and Season (WRTDS) method to assess potential changes in water quality in two watersheds draining the North Fork Big Thompson River and Buckhorn Creek in Larimer County, Colorado that were affected by the 2020 Cameron Peak Fire. WRTDS models were developed using 12 years of pre-fire data and used to estimate the expected constituent concentrations for each sample collected in the post-fire record. The predicted constituent concentrations modelled in this manner are representative of conditions in the absence of fire and allow pre-fire and post-fire stream chemistry to be quantitatively compared. Nitrate and total phosphorus concentrations showed the greatest differences between the observed and predicted concentrations, which were up to 153% greater than expected. We linked changes in source inputs and elevation as likely controls on the difference in magnitude and timing of response between the two watersheds. Post-fire arsenic and manganese concentrations were greater than the predicted concentrations in both watersheds, with arsenic up to 42% greater and manganese up to 85% greater than the model predictions. Post-fire calcium, magnesium, chloride and sulphate concentrations were greater than model predictions at the North Fork and less than the predictions at Buckhorn. We argue that greater burn severity at Buckhorn likely reduced soil–water infiltration and led to bypassed subsurface flow paths through a major lithologic source of these constituents. Post-fire changes in total organic carbon and dissolved iron concentrations were weakly supported by the model results, as observed concentrations were largely within the bounds of expected values calculated from the pre-fire model. The novel approach to WRTDS presented in this study could be a useful tool for water-quality assessments after land disturbances in the western United States.</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/hyp.70178","usgsCitation":"Ruckhaus, M.H., Clow, D.W., Hirsch, R.M., and Chapin, T.W., 2025, Characterizing water-quality response after the 2020 Cameron Peak Fire using a novel application of the Weighted Regressions on Time, Discharge, and Season method: Hydrological Processes, v. 39, no. 6, e70178, 21 p., https://doi.org/10.1002/hyp.70178.","productDescription":"e70178, 21 p.","ipdsId":"IP-171701","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":491489,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/hyp.70178","text":"Publisher Index Page"},{"id":491178,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","county":"Larimer County","otherGeospatial":"Buckhorn Creek watershed, North Fork Big Thompson River watershed","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -105.1667,\n              40.75\n            ],\n            [\n              -106,\n              40.75\n            ],\n            [\n              -106,\n              40.333\n            ],\n            [\n              -105.1667,\n              40.333\n            ],\n            [\n              -105.1667,\n              40.75\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"39","issue":"6","noUsgsAuthors":false,"publicationDate":"2025-06-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Ruckhaus, Manya Helene 0009-0006-3111-1127","orcid":"https://orcid.org/0009-0006-3111-1127","contributorId":344234,"corporation":false,"usgs":true,"family":"Ruckhaus","given":"Manya","email":"","middleInitial":"Helene","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":941103,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Clow, David W. 0000-0001-6183-4824 dwclow@usgs.gov","orcid":"https://orcid.org/0000-0001-6183-4824","contributorId":1671,"corporation":false,"usgs":true,"family":"Clow","given":"David","email":"dwclow@usgs.gov","middleInitial":"W.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":941104,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hirsch, Robert M. 0000-0002-4534-075X rhirsch@usgs.gov","orcid":"https://orcid.org/0000-0002-4534-075X","contributorId":2005,"corporation":false,"usgs":true,"family":"Hirsch","given":"Robert","email":"rhirsch@usgs.gov","middleInitial":"M.","affiliations":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":941105,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Chapin, Tanner William 0000-0003-3905-3241","orcid":"https://orcid.org/0000-0003-3905-3241","contributorId":297923,"corporation":false,"usgs":true,"family":"Chapin","given":"Tanner","email":"","middleInitial":"William","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":941106,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70273481,"text":"70273481 - 2025 - Evaluating slash piles as habitat for a threatened salamander","interactions":[],"lastModifiedDate":"2026-01-16T15:07:00.084464","indexId":"70273481","displayToPublicDate":"2025-06-16T09:02:27","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1636,"text":"Fire Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating slash piles as habitat for a threatened salamander","docAbstract":"<h3 class=\"c-article__sub-heading\" data-test=\"abstract-sub-heading\">Background</h3><p>Amplified wildfire activity in forests of the western United States threatens biodiversity. Fuel treatments can reduce fire severity, modify fire behavior, and restore forest structure and composition, yet impacts of some treatments, including slash piling and burning, on wildlife have received little attention. Piling of residual woody material may create habitable microenvironments for species that require cool, moist microclimates for all biological and ecological functions. One such species, the Sacramento Mountain salamander (<i>Aneides hardii</i><span>&nbsp;</span>Taylor), a relictual, endemic salamander narrowly distributed in the mountains of south-central New Mexico, USA, has been found below constructed slash piles within its range, but the characteristics of occupied slash piles and the extent of their occupancy has not yet been quantified. We surveyed for Sacramento Mountain salamanders in slash piles and under logs (cover objects) adjacent to piles and within a surrounding survey plot, and related salamander occupancy to slash pile and cover object characteristics, soil moisture and temperature, and environmental setting.</p><h3 class=\"c-article__sub-heading\" data-test=\"abstract-sub-heading\">Results</h3><p>We found Sacramento Mountain salamanders in 50% of surveyed slash piles. About 90% of salamanders were found in piles that contained black plastic sheeting, which held accumulations of moist leaf litter and other forest debris. We found no differences in pile characteristics, soil variables, or environmental setting between piles occupied by salamanders and piles in which no salamanders were detected. Salamander density was highest in slash piles, ~ 10% lower under cover objects in the survey area, and ~ 23% lower under cover objects adjacent to slash piles.</p><h3 class=\"c-article__sub-heading\" data-test=\"abstract-sub-heading\">Conclusions</h3><p>Slash piles serve as habitat for Sacramento Mountain salamanders. Our results suggest that within our study area or similar environments within the species range, any comparable slash pile has the potential to be occupied by salamanders. Species and habitat conservation measures indicated by this study and the timing of historical detections into mid-October include constructing smaller, pyramidal piles that minimize log-on-log or log-ground contact, avoiding the inclusion of black plastic in piles, limiting residence time of piles on the landscape, and initiating pile burning in late October or early November, when most salamanders are likely to have retreated below the ground surface.</p>","language":"English","publisher":"Springer","doi":"10.1186/s42408-025-00381-4","collaboration":"University of Rhode Island","usgsCitation":"Loehman, R.A., and Karraker, N.E., 2025, Evaluating slash piles as habitat for a threatened salamander: Fire Ecology, v. 21, 36, 18 p., https://doi.org/10.1186/s42408-025-00381-4.","productDescription":"36, 18 p.","ipdsId":"IP-124527","costCenters":[{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true}],"links":[{"id":498916,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s42408-025-00381-4","text":"Publisher Index Page"},{"id":498739,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Mexico","otherGeospatial":"Lincoln National Forest","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -105.4616018244409,\n              32.86352310900293\n            ],\n            [\n              -105.4616018244409,\n              32.775897714349966\n            ],\n            [\n              -105.30671714574738,\n              32.775897714349966\n            ],\n            [\n              -105.30671714574738,\n              32.86352310900293\n            ],\n            [\n              -105.4616018244409,\n              32.86352310900293\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"21","noUsgsAuthors":false,"publicationDate":"2025-06-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Loehman, Rachel A. 0000-0001-7680-1865 rloehman@usgs.gov","orcid":"https://orcid.org/0000-0001-7680-1865","contributorId":187605,"corporation":false,"usgs":true,"family":"Loehman","given":"Rachel","email":"rloehman@usgs.gov","middleInitial":"A.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true}],"preferred":false,"id":953895,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Karraker, Nancy E","contributorId":365192,"corporation":false,"usgs":false,"family":"Karraker","given":"Nancy","middleInitial":"E","affiliations":[{"id":6922,"text":"University of Rhode Island","active":true,"usgs":false}],"preferred":false,"id":953896,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70269051,"text":"70269051 - 2025 - Timescales of surface faulting preservation in low-strain intraplate regions from landscape evolution modeling and the geomorphic and historical record","interactions":[],"lastModifiedDate":"2025-07-15T17:01:10.189577","indexId":"70269051","displayToPublicDate":"2025-06-14T09:58:42","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":6453,"text":"Journal of Geophysical Research Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"Timescales of surface faulting preservation in low-strain intraplate regions from landscape evolution modeling and the geomorphic and historical record","docAbstract":"Large surface-rupturing intraplate earthquakes in stable continental regions (SCRs) are uncommon globally and have recurrence intervals of thousands to hundreds of thousands of years based on the paleoseismic and geomorphic record, challenging accurate active fault identification in these regions. To constrain the timescales of preservation for scarps created by surface ruptures from dip-slip earthquakes, we use a two-dimensional scarp diffusion model for typical intraplate settings and explore which parameters influence fault scarp preservation. These parameters include the coseismic vertical surface offset, the recurrence interval of similar magnitude earthquakes, diffusivity (as a proxy for mean annual precipitation rate), and the erodibility of the surficial material. We constrain parameter ranges from a compilation of historical surface ruptures in intraplate settings in a variety of climates, including the Central and Eastern United States, Australia, Europe, Central Asia (Mongolia, China), India, and West Africa. The timescales of scarp preservation from landscape evolution modeling agree well with observations of scarp preservation in low-strain SCR and intraplate tectonic settings, with some notable exceptions for Australian scarps. We find that the erodibility of the surficial material and earthquake recurrence interval have a stronger effect on the timescales of scarp preservation than diffusivity or coseismic vertical surface offset. Our model results may aid in identifying and characterizing subtle, slow-moving active faults in low-strain SCR and intraplate tectonic settings for different tectonic, geomorphic, and climatic characteristics. Accurate fault locations and characterization from the landscape record has implications for both probabilistic seismic and fault displacement hazard analyses.","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2024JB029966","usgsCitation":"Jobe, J.A., and Reitman, N.G., 2025, Timescales of surface faulting preservation in low-strain intraplate regions from landscape evolution modeling and the geomorphic and historical record: Journal of Geophysical Research Solid Earth, v. 130, no. 6, e2024JB029966, 26 p., https://doi.org/10.1029/2024JB029966.","productDescription":"e2024JB029966, 26 p.","ipdsId":"IP-169391","costCenters":[{"id":78941,"text":"Geologic Hazards Science Center - Landslides / Earthquake Geology","active":true,"usgs":true}],"links":[{"id":492286,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"130","issue":"6","noUsgsAuthors":false,"publicationDate":"2025-06-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Jobe, Jessica Ann Thompson 0000-0001-5574-4523","orcid":"https://orcid.org/0000-0001-5574-4523","contributorId":295377,"corporation":false,"usgs":true,"family":"Jobe","given":"Jessica","email":"","middleInitial":"Ann Thompson","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":943116,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Reitman, Nadine G. 0000-0002-6730-2682 nreitman@usgs.gov","orcid":"https://orcid.org/0000-0002-6730-2682","contributorId":5816,"corporation":false,"usgs":true,"family":"Reitman","given":"Nadine","email":"nreitman@usgs.gov","middleInitial":"G.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":943117,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70262138,"text":"70262138 - 2025 - Sustainability trade-offs across modeled floating solar waterscapes of the Northeastern United States","interactions":[],"lastModifiedDate":"2025-08-04T15:52:31.715077","indexId":"70262138","displayToPublicDate":"2025-06-13T09:38:53","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":21644,"text":"Cell Reports Sustainability","active":true,"publicationSubtype":{"id":10}},"title":"Sustainability trade-offs across modeled floating solar waterscapes of the Northeastern United States","docAbstract":"<p><span>Expansion of floating photovoltaic (FPV) solar systems provides a low-conflict renewable energy option to help mitigate climate change while sparing land, but potential sustainability trade-offs remain unquantified. We compare the technical potential of maximum FPV deployment to address the climate crisis with FPV-buildout scenarios that prioritize biodiversity and social values across waterscapes. FPV deployment on all technically suitable waterbodies (3.5% of available sites) in the Northeastern US could generate nearly a quarter of the region’s solar energy while offsetting all the land required for solar by 2050, but trade-offs, including maintenance of freshwater biodiversity and recreational benefits, exist. Avoidance of socioenvironmental interactions yields FPV-electricity generation potential equal to a 5% increase in regional solar generation while sparing water for biodiversity and social values, though opportunities for co-location make this a conservative estimate. Our framework extends technical potential assessments to holistically inform FPV siting and support diverse Sustainable Development Goals.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.crsus.2025.100423","usgsCitation":"Gallaher, A., Kalies, E., and Grodsky, S.M., 2025, Sustainability trade-offs across modeled floating solar waterscapes of the Northeastern United States: Cell Reports Sustainability, v. 2, no. 7, 100423, 15 p., https://doi.org/10.1016/j.crsus.2025.100423.","productDescription":"100423, 15 p.","ipdsId":"IP-166158","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":491012,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.crsus.2025.100423","text":"Publisher Index Page"},{"id":490768,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Connecticut, Delaware, Maine, Maryland, Massachusetts, New Hampshire, New Jersey, New York, Pennsylvania, Rhode Island, Vermont, Virginia, West Virginia","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"MultiPolygon\",\"coordinates\":[[[[-71.860513,41.320248],[-72.983751,41.235364],[-73.643478,41.002171],[-73.785964,40.800862],[-72.245348,41.161217],[-72.273657,41.051533],[-72.116368,40.999796],[-71.869558,41.075046],[-72.39585,40.86666],[-73.23914,40.6251],[-74.206731,40.594569],[-74.209788,40.447407],[-73.995683,40.468707],[-73.971381,40.371709],[-74.090945,39.799978],[-74.850748,38.954538],[-74.933571,38.928519],[-74.905181,39.174945],[-75.165979,39.201842],[-75.542894,39.470447],[-75.511743,39.674313],[-75.587147,39.651012],[-75.401193,39.088762],[-75.06551,38.66103],[-75.057288,38.404738],[-75.87767,37.135604],[-76.023664,37.268971],[-75.712065,37.936082],[-75.846621,37.925785],[-75.938577,38.272329],[-76.188644,38.267434],[-76.320843,38.459862],[-76.190902,38.621092],[-76.308922,38.813346],[-76.205063,38.892726],[-76.333703,38.984607],[-76.168332,38.996546],[-76.27566,39.160304],[-75.986298,39.510398],[-76.497977,39.204697],[-76.438845,39.0529],[-76.559697,38.767443],[-76.329433,38.073986],[-77.040638,38.444618],[-77.256412,38.396755],[-77.175969,38.604113],[-77.26443,38.582845],[-77.286202,38.347025],[-77.024866,38.386791],[-76.910832,38.197073],[-76.265998,37.91138],[-76.339892,37.655966],[-76.722156,37.83668],[-76.252415,37.447274],[-76.475927,37.250543],[-76.300352,37.00885],[-76.780532,37.209336],[-76.482407,36.917364],[-76.058154,36.916947],[-75.867044,36.550754],[-83.645586,36.600002],[-82.895445,36.882145],[-82.722097,37.120168],[-81.968297,37.537798],[-82.39968,37.829935],[-82.638398,38.152157],[-82.595382,38.382712],[-82.181967,38.599384],[-82.068864,38.984878],[-81.759995,38.925828],[-81.814155,39.073478],[-81.692203,39.236091],[-80.865575,39.662751],[-80.602895,40.327869],[-80.652436,40.562544],[-80.52566,40.636068],[-80.519345,41.929168],[-78.868556,42.770258],[-79.061388,43.251349],[-78.370221,43.376505],[-76.952174,43.270692],[-76.235834,43.529256],[-76.133697,43.940356],[-76.360306,44.070907],[-76.312647,44.199044],[-74.946686,44.984665],[-71.502487,45.013367],[-71.443882,45.235462],[-70.898482,45.244088],[-70.684614,45.395071],[-70.688214,45.563981],[-70.259117,45.890755],[-70.290896,46.185838],[-70.057061,46.415036],[-69.997086,46.69523],[-69.22442,47.459686],[-69.066715,47.43024],[-69.0402,47.2451],[-68.893204,47.182974],[-68.292679,47.359476],[-67.991871,47.212042],[-67.790515,47.067921],[-67.803148,45.696127],[-67.476704,45.604157],[-67.489464,45.282653],[-67.390579,45.154114],[-67.145652,45.146667],[-66.986318,44.820657],[-68.049334,44.33073],[-68.22939,44.463496],[-68.191924,44.306675],[-68.339498,44.222893],[-68.3791,44.430049],[-68.529905,44.39907],[-68.528153,44.241263],[-68.982449,44.426195],[-69.031878,44.079036],[-69.259838,43.921427],[-69.851297,43.703581],[-70.026193,43.822587],[-70.176023,43.76079],[-70.810999,42.892375],[-70.772267,42.711064],[-70.595474,42.660336],[-70.996097,42.271222],[-70.754488,42.228673],[-70.471552,41.761563],[-70.008462,41.800786],[-70.169781,42.059736],[-70.082624,42.054657],[-69.935952,41.809422],[-69.976478,41.603664],[-70.329924,41.634578],[-70.902763,41.421061],[-70.658659,41.543385],[-70.708193,41.730959],[-71.19302,41.457931],[-71.21616,41.62549],[-71.304394,41.454502],[-71.19564,41.67509],[-71.342786,41.728506],[-71.455371,41.407962],[-71.860513,41.320248]],[[-77.038598,38.791513],[-77.002498,38.96541],[-77.0915,38.95651],[-77.038598,38.791513]]],[[[-70.59628,41.471905],[-70.450431,41.420703],[-70.496162,41.346452],[-70.802083,41.314207],[-70.59628,41.471905]]],[[[-70.092142,41.297741],[-69.960277,41.278731],[-70.256164,41.288123],[-70.092142,41.297741]]],[[[-74.144428,40.53516],[-74.219787,40.502603],[-74.120186,40.642201],[-74.144428,40.53516]]]]},\"properties\":{\"name\":\"Connecticut\",\"nation\":\"USA  \"}}]}","volume":"2","issue":"7","noUsgsAuthors":false,"publicationDate":"2025-06-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Gallaher, Adam","contributorId":348210,"corporation":false,"usgs":false,"family":"Gallaher","given":"Adam","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":923251,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kalies, Elizabeth L.","contributorId":348212,"corporation":false,"usgs":false,"family":"Kalies","given":"Elizabeth L.","affiliations":[{"id":7041,"text":"The Nature Conservancy","active":true,"usgs":false}],"preferred":false,"id":923252,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Grodsky, Steven Mark 0000-0003-0846-7230","orcid":"https://orcid.org/0000-0003-0846-7230","contributorId":328517,"corporation":false,"usgs":true,"family":"Grodsky","given":"Steven","email":"","middleInitial":"Mark","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":923253,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70268216,"text":"70268216 - 2025 - Assessing nonpoint-source uranium pollution in an irrigated stream-aquifer system","interactions":[],"lastModifiedDate":"2025-06-17T14:39:24.788639","indexId":"70268216","displayToPublicDate":"2025-06-13T09:30:54","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Assessing nonpoint-source uranium pollution in an irrigated stream-aquifer system","docAbstract":"<p><span>Uranium (U) in rocks and soils of arid and semi-arid environments can be mobilized by irrigation and fertilization, posing environmental and health risks. Elevated U, along with selenium (Se) and nitrate (NO</span><sub>3</sub><span>) co-constituents, necessitates careful monitoring and management. We developed a distributed-parameter numerical model to assess U pollution in an irrigated stream-aquifer system, applying it to a 552&nbsp;km</span><sup>2</sup><span>&nbsp;region in Colorado's Lower Arkansas River Valley (LARV) over 14&nbsp;years. A MODFLOW model, describing groundwater and stream flow, was coupled with an RT3D-OTIS model to portray reactive U transport. Calibration using the PESTPP-iES iterative ensemble smoother (iES) software indicated good agreement with observed U concentrations. The model revealed substantial and variable U levels across the LARV, highlighting potential hotspots and possible contributing factors, such as geological composition of the bedrock and near-surface shale and aquifer sediments derived from them, irrigation practices, and riparian landscape. U levels exceed the chronic standard (85th percentile&nbsp;=&nbsp;30&nbsp;μg/L, set by the US Environmental Protection Agency), which is the permissible regulatory threshold, in groundwater across 44&nbsp;% of the region and along the river by an average factor of 2.9. Simulated average U concentrations in the non-riparian aquifer and river are 124&nbsp;μg/L and 60&nbsp;μg/L, respectively, compared with 112&nbsp;μg/L and 62&nbsp;μg/L for measured values. The average 85th percentile U concentration is 222&nbsp;μg/L in the aquifer and 82&nbsp;μg/L in the river. Average simulated U mass loading to the river is 0.17&nbsp;kg/day per km, compared to an estimated 0.23&nbsp;kg/day per km. Findings provide a baseline for comparing future simulated outcomes of alternative best management practices (BMPs) for U pollution mitigation and offer a methodology applicable to other irrigated regions.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2025.179861","usgsCitation":"Qurban, I., Gates, T., Morway, E.D., Cox, J., White, J., Bailey, R.T., and Fienen, M., 2025, Assessing nonpoint-source uranium pollution in an irrigated stream-aquifer system: Science of the Total Environment, v. 989, 179861, 22 p., https://doi.org/10.1016/j.scitotenv.2025.179861.","productDescription":"179861, 22 p.","ipdsId":"IP-165259","costCenters":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"links":[{"id":490987,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2025.179861","text":"Publisher Index Page"},{"id":490832,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Lower Arkansas River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -104.84418826977637,\n              38.499618485687876\n            ],\n            [\n              -104.84418826977637,\n              37.73373680491562\n            ],\n            [\n              -102.09264905018665,\n              37.73373680491562\n            ],\n            [\n              -102.09264905018665,\n              38.499618485687876\n            ],\n            [\n              -104.84418826977637,\n              38.499618485687876\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"989","noUsgsAuthors":false,"publicationDate":"2025-06-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Qurban, Ibraheem A.","contributorId":356917,"corporation":false,"usgs":false,"family":"Qurban","given":"Ibraheem A.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":940473,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gates, Timothy K. 0000-0003-4702-4395","orcid":"https://orcid.org/0000-0003-4702-4395","contributorId":356920,"corporation":false,"usgs":false,"family":"Gates","given":"Timothy K.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":940474,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":940475,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cox, John T. 0000-0002-2956-0285","orcid":"https://orcid.org/0000-0002-2956-0285","contributorId":356923,"corporation":false,"usgs":false,"family":"Cox","given":"John T.","affiliations":[{"id":85282,"text":"W.W. Wheeler & Associates","active":true,"usgs":false}],"preferred":false,"id":940476,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"White, Jeremy T. 0000-0002-4950-1469","orcid":"https://orcid.org/0000-0002-4950-1469","contributorId":248830,"corporation":false,"usgs":false,"family":"White","given":"Jeremy T.","affiliations":[{"id":50032,"text":"GNS New Zealand","active":true,"usgs":false}],"preferred":false,"id":940477,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bailey, Ryan T. 0000-0002-6539-1474","orcid":"https://orcid.org/0000-0002-6539-1474","contributorId":204129,"corporation":false,"usgs":false,"family":"Bailey","given":"Ryan","email":"","middleInitial":"T.","affiliations":[{"id":36859,"text":"Colorado State University, Department of Civil and Environmental Engineerring","active":true,"usgs":false}],"preferred":false,"id":940478,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Fienen, Michael N. 0000-0002-7756-4651","orcid":"https://orcid.org/0000-0002-7756-4651","contributorId":245632,"corporation":false,"usgs":true,"family":"Fienen","given":"Michael N.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":940479,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70268357,"text":"70268357 - 2025 - Canopy and surface fuels measurement using terrestrial lidar single-scan approach in the Mogollon highlands of Arizona","interactions":[],"lastModifiedDate":"2025-06-23T14:08:47.814199","indexId":"70268357","displayToPublicDate":"2025-06-13T09:03:19","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2083,"text":"International Journal of Wildland Fire","active":true,"publicationSubtype":{"id":10}},"title":"Canopy and surface fuels measurement using terrestrial lidar single-scan approach in the Mogollon highlands of Arizona","docAbstract":"<div class=\"section\"><strong>Background</strong><p id=\"d6e253\">Fuel monitoring data are essential to evaluate wildfire risk, plan management activities and evaluate fuel treatment effects. Terrestrial light detection and ranging (lidar) is a field-based 3D scanning technology with great potential to reduce labor-intensive field measurements and provide new depths of vegetation structure data.</p></div><div class=\"section\"><strong>Aims</strong><p id=\"d6e258\">To facilitate the integration of terrestrial lidar into fuel monitoring programs, we developed a model, training process, and Python program that produces canopy fuel, surface fuel and terrain metrics commonly used in fire behavior and fire risk modeling.</p></div><div class=\"section\"><strong>Methods</strong><p id=\"d6e263\">We estimated canopy and surface fuel metrics from terrestrial lidar using a semi-empirical model incorporating physically based modeling of leaf area density and occlusion and a non-destructive model calibration process leveraging Bayesian regression. We compared lidar-derived fuel estimates with conventional fuel estimates across diverse conditions in semi-arid shrubland, woodland and forest in Arizona. We also compared estimates using single- and multiple-scan modes.</p></div><div class=\"section\"><strong>Key results</strong><p id=\"d6e268\">In single-scan mode, our lidar-derived fuel estimates were significantly related to conventional estimates of total canopy fuel load, maximum canopy bulk density, downed surface fuel load and standing surface fuel load.</p></div><div class=\"section\"><strong>Implications</strong><p id=\"d6e273\">Our methods provide opportunities to increase the scalability of fuel monitoring to better understand wildfire risk and treatment effectiveness.</p></div>","language":"English","publisher":"CSIRO Publishing","doi":"10.1071/WF24221","usgsCitation":"Tenny, J., Sankey, T.T., Munson, S.M., Sánchez Meador, A., and Goetz, S.J., 2025, Canopy and surface fuels measurement using terrestrial lidar single-scan approach in the Mogollon highlands of Arizona: International Journal of Wildland Fire, v. 34, no. 7, WF24221, 15 p., https://doi.org/10.1071/WF24221.","productDescription":"WF24221, 15 p.","ipdsId":"IP-172468","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":491454,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1071/wf24221","text":"Publisher Index Page"},{"id":491095,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Mogollon Highlands","volume":"34","issue":"7","noUsgsAuthors":false,"publicationDate":"2025-06-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Tenny, Johnathan T.","contributorId":357286,"corporation":false,"usgs":false,"family":"Tenny","given":"Johnathan T.","affiliations":[{"id":85397,"text":"School of Informatics, Computing, and Cyber Systems, Northern Arizona University, 1298 S. Knoles Drive, Flagstaff, AZ 86011, United States","active":true,"usgs":false}],"preferred":false,"id":941069,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sankey, Temuulen Tsagaan","contributorId":149290,"corporation":false,"usgs":false,"family":"Sankey","given":"Temuulen","email":"","middleInitial":"Tsagaan","affiliations":[],"preferred":false,"id":941070,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Munson, Seth M. 0000-0002-2736-6374 smunson@usgs.gov","orcid":"https://orcid.org/0000-0002-2736-6374","contributorId":1334,"corporation":false,"usgs":true,"family":"Munson","given":"Seth","email":"smunson@usgs.gov","middleInitial":"M.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true},{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":941071,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sánchez Meador, Andrew J.","contributorId":357287,"corporation":false,"usgs":false,"family":"Sánchez Meador","given":"Andrew J.","affiliations":[{"id":85399,"text":"School of Forestry, Northern Arizona University, Flagstaff, Arizona, United States; Ecological Restoration Institute, Northern Arizona University, Flagstaff, Arizona, United States","active":true,"usgs":false}],"preferred":false,"id":941072,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Goetz, Scott J.","contributorId":222547,"corporation":false,"usgs":false,"family":"Goetz","given":"Scott","email":"","middleInitial":"J.","affiliations":[{"id":40559,"text":"School of Informatics, Computing, and Cyber Systems, Northern Arizona University, Flagstaff, AZ","active":true,"usgs":false}],"preferred":false,"id":941073,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70268346,"text":"70268346 - 2025 - Diamondback terrapin resource use in a seagrass-dominated coastal bay varies by life stage","interactions":[],"lastModifiedDate":"2025-06-23T14:02:40.885581","indexId":"70268346","displayToPublicDate":"2025-06-13T08:58:06","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1584,"text":"Estuaries and Coasts","active":true,"publicationSubtype":{"id":10}},"title":"Diamondback terrapin resource use in a seagrass-dominated coastal bay varies by life stage","docAbstract":"<p><span>Diamondback terrapins, hereafter referred to as terrapins, are the only estuarine turtle species native to North America. However, terrapins are also occasionally found in marine habitats, such as seagrass beds, and yet little is known about how they use those marine habitats. We sampled epidermis from terrapins (</span><i>Malaclemys terrapin macrospilota</i><span>) inhabiting a seagrass-dominated coastal bay in Northwest Florida and compared resource use among terrapin sexes and life-history stages using the isotopic niche and mixing models. Terrapins were generalist foragers, and their diets varied by sex and life stage, as has been reported elsewhere. Basal resource mixing models indicated the terrapin food web was based primarily on&nbsp;</span><i>Thalassia testudinum</i><span>&nbsp;for adult females (50.0%) and&nbsp;</span><i>Spartina alterniflora</i><span>&nbsp;for adult males (49.7%) and juvenile females (42.2%). Dietary mixing models indicated the adult female diet included a relatively high proportion of&nbsp;</span><i>Thalassia testudinum</i><span>&nbsp;(31.3%), suggesting a strong reliance on seagrass dominated prey and not necessarily large consumption of seagrass, followed by lower proportions of gastropods (26.6%) and crustaceans (19.1%). Primary diet items for juvenile females and adult males included relatively equal proportions of echinoderms, gastropods, crustaceans, ascidians, and porifera. Body and head size of terrapins may drive differences in diet, as interpreted from mixing model results. Although mangroves are expanding their range northward along the Gulf of America coast and have become established at our study site, it does not appear that terrapins are foraging within these newly established mangrove forests. Finally, the terrapin niche, particularly for adult females, may overlap with the sea turtle niche in seagrass-dominated bays. Whether sea turtles impact terrapin populations, including through direct predation, is unknown.</span></p>","language":"English","publisher":"Springer Nature","doi":"10.1007/s12237-025-01568-3","usgsCitation":"Lamont, M., Arends, C.L., Catizone, D.J., and Vander Zanden, H.B., 2025, Diamondback terrapin resource use in a seagrass-dominated coastal bay varies by life stage: Estuaries and Coasts, v. 48, no. 5, 132, 12 p., https://doi.org/10.1007/s12237-025-01568-3.","productDescription":"132, 12 p.","ipdsId":"IP-169842","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":491453,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s12237-025-01568-3","text":"Publisher Index Page"},{"id":491094,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"St. Joseph Bay","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -85.42067407815058,\n              29.88845033015012\n            ],\n            [\n              -85.42067407815058,\n              29.67807911729524\n            ],\n            [\n              -85.28516563300288,\n              29.67807911729524\n            ],\n            [\n              -85.28516563300288,\n              29.88845033015012\n            ],\n            [\n              -85.42067407815058,\n              29.88845033015012\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"48","issue":"5","noUsgsAuthors":false,"publicationDate":"2025-06-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Lamont, Margaret 0000-0001-7520-6669","orcid":"https://orcid.org/0000-0001-7520-6669","contributorId":206817,"corporation":false,"usgs":true,"family":"Lamont","given":"Margaret","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":940893,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Arends, Carson L. 0000-0001-9962-8647","orcid":"https://orcid.org/0000-0001-9962-8647","contributorId":296689,"corporation":false,"usgs":true,"family":"Arends","given":"Carson","email":"","middleInitial":"L.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":940894,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Catizone, Daniel J. 0000-0002-7030-4208","orcid":"https://orcid.org/0000-0002-7030-4208","contributorId":248817,"corporation":false,"usgs":true,"family":"Catizone","given":"Daniel","email":"","middleInitial":"J.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":940895,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Vander Zanden, Hannah B.","contributorId":138885,"corporation":false,"usgs":false,"family":"Vander Zanden","given":"Hannah","email":"","middleInitial":"B.","affiliations":[{"id":12562,"text":"Department of Geology and Geophysics, University of Utah; Archie Carr Center for Sea Turtle Research, University of Florida","active":true,"usgs":false}],"preferred":false,"id":940896,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70268146,"text":"70268146 - 2025 - Multi-model comparison of salt marsh longevity under relative sea-level rise","interactions":[],"lastModifiedDate":"2025-06-16T13:57:23.958198","indexId":"70268146","displayToPublicDate":"2025-06-13T08:52:26","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1584,"text":"Estuaries and Coasts","active":true,"publicationSubtype":{"id":10}},"title":"Multi-model comparison of salt marsh longevity under relative sea-level rise","docAbstract":"<p><span>Understanding salt marsh resilience under increasing sea levels can inform for management decisions. We compared temporal projections from various wetland process-based models and a geospatially derived metric (i.e., marsh lifespan) to understand key considerations and uncertainties about salt marsh resilience when using these products for decision-making. The influences of lidar topographic correction and marsh surface sediment accretion were explored across a suite of relative sea level rise (RSLR) projections to assess differences in the timing and amount of habitat change for each modeling approach. All models were run for a small coastal wetland site located in the Chesapeake Bay, Maryland, USA, to assess potential change in marsh habitat, and timing of marsh loss due to RSLR. All modeling results agreed that marsh longevity was threatened by RSLR but they varied in the time of predicted marsh submergence between the years 2070 and 2100 depending on the initial marsh surface elevation and accretion rates. Models with similar accretion rates predicted similar years until marsh submergence. Removing a positive elevation bias from lidar surveys in densely vegetated marsh areas for these models resulted in onset of submergence ~ 7 years earlier. Because there are many tradeoffs to each model type, end users need to evaluate management questions, overall goals, the amount of effort involved in model parameterization, and the amount of uncertainty in the model that they are willing to accept.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s12237-025-01559-4","usgsCitation":"Martinez, M., Buffington, K., Ganju, N., Defne, Z., Ackerman, K., Thorne, K., Guntenspergen, G.R., and Carr, J., 2025, Multi-model comparison of salt marsh longevity under relative sea-level rise: Estuaries and Coasts, v. 48, 131, 17 p., https://doi.org/10.1007/s12237-025-01559-4.","productDescription":"131, 17 p.","ipdsId":"IP-175115","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":491006,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s12237-025-01559-4","text":"Publisher Index Page"},{"id":490750,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maryland","county":"Kent County","otherGeospatial":"Eastern Neck Island National Wildlife Refuge","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -76.24030263498597,\n              39.05092670969253\n            ],\n            [\n              -76.2464251064265,\n              39.02623477098268\n            ],\n            [\n              -76.22111104181657,\n              39.0091277190638\n            ],\n            [\n              -76.20939592819497,\n              39.005880153850384\n            ],\n            [\n              -76.19532601786523,\n              39.010317858728\n            ],\n            [\n              -76.20639356239224,\n              39.05275533676962\n            ],\n            [\n              -76.22099330198093,\n              39.05568114506616\n            ],\n            [\n              -76.24030263498597,\n              39.05092670969253\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"48","noUsgsAuthors":false,"publicationDate":"2025-06-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Martinez, Melinda 0000-0001-6652-9220","orcid":"https://orcid.org/0000-0001-6652-9220","contributorId":290467,"corporation":false,"usgs":true,"family":"Martinez","given":"Melinda","email":"","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":940339,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Buffington, Kevin J. 0000-0001-9741-1241 kbuffington@usgs.gov","orcid":"https://orcid.org/0000-0001-9741-1241","contributorId":4775,"corporation":false,"usgs":true,"family":"Buffington","given":"Kevin","email":"kbuffington@usgs.gov","middleInitial":"J.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":940340,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ganju, Neil K. 0000-0002-1096-0465","orcid":"https://orcid.org/0000-0002-1096-0465","contributorId":202878,"corporation":false,"usgs":true,"family":"Ganju","given":"Neil K.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":940341,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Defne, Zafer 0000-0003-4544-4310 zdefne@usgs.gov","orcid":"https://orcid.org/0000-0003-4544-4310","contributorId":5520,"corporation":false,"usgs":true,"family":"Defne","given":"Zafer","email":"zdefne@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":940342,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ackerman, Kate 0000-0003-3925-721X","orcid":"https://orcid.org/0000-0003-3925-721X","contributorId":293631,"corporation":false,"usgs":true,"family":"Ackerman","given":"Kate","email":"","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":940343,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Thorne, Karen M. 0000-0002-1381-0657","orcid":"https://orcid.org/0000-0002-1381-0657","contributorId":204579,"corporation":false,"usgs":true,"family":"Thorne","given":"Karen M.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":940344,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Guntenspergen, Glenn R. 0000-0002-8593-0244 glenn_guntenspergen@usgs.gov","orcid":"https://orcid.org/0000-0002-8593-0244","contributorId":2885,"corporation":false,"usgs":true,"family":"Guntenspergen","given":"Glenn","email":"glenn_guntenspergen@usgs.gov","middleInitial":"R.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":940345,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Carr, Joel A. 0000-0002-9164-4156 jcarr@usgs.gov","orcid":"https://orcid.org/0000-0002-9164-4156","contributorId":168645,"corporation":false,"usgs":true,"family":"Carr","given":"Joel A.","email":"jcarr@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":940346,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70268148,"text":"70268148 - 2025 - Not all spatially structured populations are metapopulations: Re-examining paradigms for a threatened shorebird","interactions":[],"lastModifiedDate":"2025-06-16T13:43:43.023749","indexId":"70268148","displayToPublicDate":"2025-06-13T08:35:54","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"Not all spatially structured populations are metapopulations: Re-examining paradigms for a threatened shorebird","docAbstract":"<p><span>For at-risk species, understanding population vital rates is imperative for developing informed conservation strategies and population models. Managers often assume that species that are spatially distributed among patches of suitable habitat meet the criteria of a metapopulation. Metapopulation dynamics are determined not only by within-patch birth and death processes but also by between-patch dispersal movements of individuals that are infrequent but critical to maintaining population viability across space and time. To conserve and manage such species, an understanding of all these vital rates, including connectivity, is required. The degree to which the northern Great Plains piping plover (</span><i>Charadrius melodus</i><span>) breeding population functions as a metapopulation depends, in part, on the rate of movement among patchily distributed breeding areas. Here, we examined annual adult survival and breeding dispersal probabilities for 2582 individuals at two spatial scales within the northern Great Plains piping plover breeding population between 2014 and 2019. Inconsistent with a metapopulation structure, annual survival varied minimally among breeding regions but did vary across years. We also found that breeding dispersal probabilities were temporally variable, high, and unbalanced at both spatial scales examined, suggesting high connectivity in contrast to metapopulation dynamics. Further, we detected context-dependent effects of reproductive success on dispersal decisions. Individuals were more likely to disperse from the northern Missouri River to the US Alkali Wetlands following nest failure due to inundation or severe storms (including in the year prior to dispersal), whereas dispersal from the US Alkali Wetlands to the northern Missouri River decreased following successful nest attempts. Individuals also decreased dispersal from the US Alkali Wetlands to the northern Missouri River in response to renesting attempts in both the year of interest and the year prior to dispersal. Our results contradict the paradigm that northern Great Plains piping plovers are structured as a metapopulation and instead suggest a patchily distributed, likely panmictic, population. Our findings have implications for the conservation and management of this listed species and are also a general reminder that in the absence of robust knowledge of movement, spatial variation in birth and death processes across patches should not be conflated with a metapopulation structure.</span></p>","language":"English","publisher":"Ecological Society of America","doi":"10.1002/eap.70037","usgsCitation":"Swift, R.J., Anteau, M.J., Ellis, K.S., MacDonald, G.J., Ring, M., Sherfy, M.H., Toy, D.L., and Koons, D.N., 2025, Not all spatially structured populations are metapopulations: Re-examining paradigms for a threatened shorebird: Ecological Applications, v. 35, no. 4, e70037, 22 p., https://doi.org/10.1002/eap.70037.","productDescription":"e70037, 22 p.","ipdsId":"IP-159633","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":491308,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P145PZKB","text":"USGS data release","linkHelpText":"Piping plover adult breeding dispersal and annual survival in the northern Great Plains, USA, model code"},{"id":491004,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/eap.70037","text":"Publisher Index Page"},{"id":490748,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana, North Dakota, South Dakota","otherGeospatial":"Missouri River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -103.64188754784932,\n              48.98153164866767\n            ],\n            [\n              -105.33724717279092,\n              48.994467973542584\n            ],\n            [\n      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manteau@usgs.gov","orcid":"https://orcid.org/0000-0002-5173-5870","contributorId":3427,"corporation":false,"usgs":true,"family":"Anteau","given":"Michael","email":"manteau@usgs.gov","middleInitial":"J.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":940355,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ellis, Kristen S. 0000-0003-2759-3670","orcid":"https://orcid.org/0000-0003-2759-3670","contributorId":251877,"corporation":false,"usgs":true,"family":"Ellis","given":"Kristen","email":"","middleInitial":"S.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":940356,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"MacDonald, Garrett J. 0000-0002-9487-7721","orcid":"https://orcid.org/0000-0002-9487-7721","contributorId":238820,"corporation":false,"usgs":true,"family":"MacDonald","given":"Garrett","email":"","middleInitial":"J.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":940357,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ring, Megan M. 0000-0001-8331-8492","orcid":"https://orcid.org/0000-0001-8331-8492","contributorId":225026,"corporation":false,"usgs":true,"family":"Ring","given":"Megan M.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":940358,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sherfy, Mark H. 0000-0003-3016-4105 msherfy@usgs.gov","orcid":"https://orcid.org/0000-0003-3016-4105","contributorId":125,"corporation":false,"usgs":true,"family":"Sherfy","given":"Mark","email":"msherfy@usgs.gov","middleInitial":"H.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":940359,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Toy, Dustin L. 0000-0001-5390-5784 dtoy@usgs.gov","orcid":"https://orcid.org/0000-0001-5390-5784","contributorId":5150,"corporation":false,"usgs":true,"family":"Toy","given":"Dustin","email":"dtoy@usgs.gov","middleInitial":"L.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":940360,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Koons, David N.","contributorId":28137,"corporation":false,"usgs":false,"family":"Koons","given":"David","email":"","middleInitial":"N.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":940361,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70268061,"text":"cir1556 - 2025 - U.S. Geological Survey Pollinator Science Strategy, 2025–35—A Review and Look Forward","interactions":[],"lastModifiedDate":"2025-12-15T18:12:11.353795","indexId":"cir1556","displayToPublicDate":"2025-06-12T12:33:57","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":307,"text":"Circular","code":"CIR","onlineIssn":"2330-5703","printIssn":"1067-084X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1556","title":"U.S. Geological Survey Pollinator Science Strategy, 2025–35—A Review and Look Forward","docAbstract":"<p>This “U.S. Geological Survey Pollinator Science Strategy, 2025–35—A Review and Look Forward” (“Pollinator Science Strategy”) describes the science vision of the U.S. Geological Survey (USGS) to support management, conservation, and policy decisions on animal pollinators and their habitats. As the science arm of the Department of the Interior, the USGS has a primary role in providing scientific information to natural resource managers and policymakers across the United States. This “Pollinator Science Strategy” was drafted by a team of USGS pollinator researchers and was further developed through feedback from Federal, State, Tribal, nongovernmental organizations, and industry partners. This “Pollinator Science Strategy” highlights the USGS’s role in the research to promote healthy pollinator populations and address partner information gaps so they can make more informed management decisions. By outlining the importance of USGS science in addressing the information needs of other agencies, organizations, and the public, the “Pollinator Science Strategy” reaffirms the USGS’s commitment to pollinator research and showcases our research priorities for 2025–35.</p><p>With more than 300 research centers nationally, the USGS is equipped to address pollinator science across scales of complexity and geographic range. USGS pollinator science is organized according to the following five thematic areas:</p><ol><li>Assessing species ecology, distributions, and natural history requirements.</li><li>Tracking species status and trends.</li><li>Understanding species threats and stressors.</li><li>Informing restoration and management actions.</li><li>Developing novel methods for improving pollinator research, monitoring, and population outcomes that can benefit our Nation.</li></ol><p>Our pollinator information products and associated data are made widely available to the public to ensure scientific transparency and accessibility. This “Pollinator Science Strategy” concludes with several research goals that the USGS will work towards from 2025 to 2035, representing our vision for USGS science. These research goals include synthesizing and modernizing the latest information on pollinator threats, developing research that assists managers with habitat design and restoration, providing training to partners on native bee identification and monitoring design, and developing new technologies for assessing the status and trends of our nation’s pollinators.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/cir1556","usgsCitation":"Otto, C.R.V., Graves, T.A., Robertson-Thompson, D., Pearse, I., Thogmartin, W.E., Murphy, C., Webb, L., Droege, S., Steinkamp, M., and Grundel, R., 2025, U.S. Geological Survey Pollinator Science Strategy, 2025–35—A review and look forward (ver. 1.1, June 26, 2025): U.S. Geological Survey Circular 1556, 16 p., https://doi.org/10.3133/cir1556.","productDescription":"vi, 16 p.","numberOfPages":"26","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-172990","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true},{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true},{"id":5057,"text":"NGTOC Reston","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true},{"id":65882,"text":"Midwest Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":490448,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/circ/1556/images/"},{"id":490447,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/circ/1556/circ1556.XML"},{"id":490449,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/cir1556/full"},{"id":490446,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/circ/1556/circ1556.pdf","text":"Report","size":"26 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Cir 1556"},{"id":490445,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/circ/1556/coverthb4.jpg"},{"id":491238,"rank":6,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/circ/1556/versionHist.txt","size":"1 KB","linkFileType":{"id":2,"text":"txt"}}],"edition":"Version 1.0: June 12, 2025; Version 1.1: June 26, 2025","contact":"<p>Director, <a href=\"https://www.usgs.gov/centers/npwrc\" data-mce-href=\"https://www.usgs.gov/centers/npwrc\">Northern Prairie Wildlife Research Center</a><br>U.S. Geological Survey<br>8711 37th Street Southeast<br>Jamestown, ND 58401</p><p><a href=\"https://pubs.usgs.gov/contact\" data-mce-href=\"../contact\">Contact Pubs Warehouse</a></p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Executive Summary</li><li>U.S. Geological Survey Pollinator Science Mission Statement</li><li>Importance of Pollinators</li><li>Need for Pollinator Science</li><li>U.S. Geological Survey Role in Pollinator Science</li><li>U.S. Geological Survey Pollinator Science Themes</li><li>U.S. Geological Survey Partner Science</li><li>Future Research Objectives, Actions, and Benefits</li><li>Summary</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2025-06-12","revisedDate":"2025-06-26","noUsgsAuthors":false,"publicationDate":"2025-06-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Otto, Clint 0000-0002-7582-3525 cotto@usgs.gov","orcid":"https://orcid.org/0000-0002-7582-3525","contributorId":5426,"corporation":false,"usgs":true,"family":"Otto","given":"Clint","email":"cotto@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":940091,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Graves, Tabitha A. 0000-0001-5145-2400","orcid":"https://orcid.org/0000-0001-5145-2400","contributorId":202084,"corporation":false,"usgs":true,"family":"Graves","given":"Tabitha A.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":940092,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Robertson-Thompson, Desi 0009-0003-6878-2539","orcid":"https://orcid.org/0009-0003-6878-2539","contributorId":356794,"corporation":false,"usgs":true,"family":"Robertson-Thompson","given":"Desi","affiliations":[{"id":65882,"text":"Midwest Climate Adaptation Science Center","active":true,"usgs":true}],"preferred":true,"id":940093,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pearse, Ian S. 0000-0001-7098-0495","orcid":"https://orcid.org/0000-0001-7098-0495","contributorId":216680,"corporation":false,"usgs":true,"family":"Pearse","given":"Ian","middleInitial":"S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":940094,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"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":940095,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Murphy, Caroline E. 0009-0001-9485-4730","orcid":"https://orcid.org/0009-0001-9485-4730","contributorId":334933,"corporation":false,"usgs":true,"family":"Murphy","given":"Caroline","email":"","middleInitial":"E.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":940096,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Webb, Elisabeth B. 0000-0003-3851-6056 ewebb@usgs.gov","orcid":"https://orcid.org/0000-0003-3851-6056","contributorId":3981,"corporation":false,"usgs":true,"family":"Webb","given":"Elisabeth","email":"ewebb@usgs.gov","middleInitial":"B.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":940097,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Droege, Sam 0000-0003-4393-0403","orcid":"https://orcid.org/0000-0003-4393-0403","contributorId":64185,"corporation":false,"usgs":true,"family":"Droege","given":"Sam","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":false,"id":940098,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Steinkamp, Melanie J. 0000-0001-9322-609X","orcid":"https://orcid.org/0000-0001-9322-609X","contributorId":292474,"corporation":false,"usgs":true,"family":"Steinkamp","given":"Melanie","email":"","middleInitial":"J.","affiliations":[{"id":5057,"text":"NGTOC Reston","active":true,"usgs":true}],"preferred":true,"id":940101,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Grundel, Ralph 0000-0002-2949-7087 rgrundel@usgs.gov","orcid":"https://orcid.org/0000-0002-2949-7087","contributorId":2444,"corporation":false,"usgs":true,"family":"Grundel","given":"Ralph","email":"rgrundel@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":940100,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70268224,"text":"70268224 - 2025 - Hydraulic connectivity and hydrochemistry influence microbial community structure in agriculturally-affected alluvial aquifers in the Midwestern United States","interactions":[],"lastModifiedDate":"2025-07-10T14:55:33.936187","indexId":"70268224","displayToPublicDate":"2025-06-12T09:53:23","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5925,"text":"Environmental Science and Technology","active":true,"publicationSubtype":{"id":10}},"title":"Hydraulic connectivity and hydrochemistry influence microbial community structure in agriculturally-affected alluvial aquifers in the Midwestern United States","docAbstract":"<p><span>Alluvial aquifers can provide ecosystem services and drinking water, but much remains unknown about human effects on aquifer microbiomes. Therefore, we used amplicon sequencing and hydrochemical characterization to pair microbial communities with environmental conditions across 37 alluvial aquifer wells. The study region spanned eastern Iowa and southern Minnesota (USA) and contained a combination of drinking water and monitoring wells. In terms of microbial ecology, dominant phyla across the wells included Proteobacteria, Bacteroidota, Patescibacteria, Planctomycetota, and Nitrospirota. Tritium, an indicator of infiltration and surface water influence, was the highest correlated variable with the Shannon index (α-diversity) by the Spearman rank sum (ρ = 0.60) and one of only four significant environmental variables in the constrained correspondence analysis. We built random forest regression models to predict tritium concentrations from microbial family relative abundance (held-out testing coefficient of determination (</span><i>R</i><sup>2</sup><span>) = 0.77 and mean absolute percentage error = 7%) and interpreted the models with Shapley additive explanation values. The most important families for predicting tritium concentrations were&nbsp;</span><i>Nitrosopumilaceae</i><span>&nbsp;and&nbsp;</span><i>Methylomirabilaceae</i><span>. Upwelling methane could contribute to the unusual coupling of ammonia oxidation by&nbsp;</span><i>Nitrosopumilaceae</i><span>&nbsp;with simultaneous nitrite-dependent methane oxidation by&nbsp;</span><i>Methylomirabilaceae</i><span>. Taken together, we illuminate the relationship among hydrochemistry, hydraulic connectivity, and alluvial aquifer microbiomes.</span></p>","language":"English","publisher":"ACS Publications","doi":"10.1021/acs.est.5c03155","usgsCitation":"Schroer, H., Markland, K.M., Ling, F., and Just, C.L., 2025, Hydraulic connectivity and hydrochemistry influence microbial community structure in agriculturally-affected alluvial aquifers in the Midwestern United States: Environmental Science and Technology, v. 59, no. 24, p. 12279-12291, https://doi.org/10.1021/acs.est.5c03155.","productDescription":"13 p.","startPage":"12279","endPage":"12291","ipdsId":"IP-169344","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":490912,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":490985,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1021/acs.est.5c03155","text":"Publisher Index Page"}],"country":"United States","state":"Iowa, Minnesota","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -91.83164241356687,\n              40.76134763192243\n            ],\n            [\n              -91.10093521849011,\n              40.76936587633509\n            ],\n            [\n              -90.98444609847996,\n              41.11334070983898\n            ],\n            [\n              -91.07975626082516,\n              41.37610567914743\n            ],\n            [\n              -90.60321047132624,\n              41.542769354616865\n            ],\n            [\n              -90.25374320174629,\n              41.8669244399662\n            ],\n            [\n              -93.07065717548669,\n              43.93016784084011\n            ],\n            [\n              -93.73782127267788,\n              43.983536010475774\n            ],\n            [\n              -93.97079768432694,\n              42.314858946682534\n            ],\n            [\n              -93.85431056836552,\n              41.92210428808144\n            ],\n            [\n              -91.83164241356687,\n              40.76134763192243\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"59","issue":"24","noUsgsAuthors":false,"publicationDate":"2025-06-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Schroer, Hunter","contributorId":356950,"corporation":false,"usgs":false,"family":"Schroer","given":"Hunter","affiliations":[{"id":85293,"text":"Civil, Architectural and Environmental Engineering, Missouri University of Science and Technology","active":true,"usgs":false}],"preferred":false,"id":940520,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Markland, Kendra M. 0000-0002-0276-8684 kmarkland@usgs.gov","orcid":"https://orcid.org/0000-0002-0276-8684","contributorId":306212,"corporation":false,"usgs":true,"family":"Markland","given":"Kendra","email":"kmarkland@usgs.gov","middleInitial":"M.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":940521,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ling, Fangqiong","contributorId":356951,"corporation":false,"usgs":false,"family":"Ling","given":"Fangqiong","affiliations":[{"id":85296,"text":"Department of Energy, Environmental, & Chemical Engineering, Washington University in St. Louis","active":true,"usgs":false}],"preferred":false,"id":940522,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Just, Craig L.","contributorId":178037,"corporation":false,"usgs":false,"family":"Just","given":"Craig","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":940523,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70268380,"text":"70268380 - 2025 - Assimilation of reduced carbon triggers platinum alloy saturation in mafic and ultramafic magmas","interactions":[],"lastModifiedDate":"2025-08-04T15:53:27.169903","indexId":"70268380","displayToPublicDate":"2025-06-12T09:09:33","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1472,"text":"Economic Geology","active":true,"publicationSubtype":{"id":10}},"title":"Assimilation of reduced carbon triggers platinum alloy saturation in mafic and ultramafic magmas","docAbstract":"<p><span>It is generally observed that magmatic sulfide ores have higher ratios of Pd/Pt than the mantle-like values of their parental magmas. This discrepancy has defied simple explanation because the partitioning behavior of both elements between sulfide and silicate liquids is very similar. Assimilation of sulfur- and carbon-rich country rocks by mafic and ultramafic magmas is considered a critical, if not essential, step in the formation of magmatic base metal sulfide deposits. Although there is general consensus that the assimilation of external sulfur and carbon promotes sulfide saturation, the effect of carbon assimilation on the solubilities of platinum-group elements in natural S-bearing silicate melt has been overlooked. In this study, we investigate the variations of platinum and palladium solubilities during assimilation of graphite and methane through thermodynamic modeling, in comparison with data from an array of highly distinctive magmatic sulfide ore systems representing ages from Archean to Paleozoic, melt compositions from komatiite to basalt, and magmatic settings including lavas, hypabyssal intrusions, plutonic continental arc roots, and plutonic layered intrusions, namely: Raglan, Norilsk-Talnakh, Lac des Iles, and the J-M Reef of the Stillwater Complex. We model assimilation-fractional crystallization processes to estimate the reduction of oxygen fugacity (</span><span class=\"inline-formula no-formula-id\">⁠fO2⁠</span><span>) of the melt due to incorporation of graphite and methane. The simulations show that although Pd remains highly soluble during the progressive assimilation of reduced carbon, Pt solubility decreases significantly as the silicate melt becomes increasingly reduced. With less than 8</span><i>%</i><span>&nbsp;of sediment assimilation, Pt alloy may saturate and then deviate from sulfide-undersaturated silicate melts, concomitantly increasing the Pd/Pt value of the remaining melts of the Raglan and Norilsk-Talnakh systems. For the Lac des Iles and Stillwater systems, a higher extent of assimilation is needed to reach Pt saturation because of the relatively carbon-poor nature of the lower crustal rocks. The assimilation of methane volatiles is shown to be more effective than graphite assimilation, and it provides a pathway to Pt alloy fractionation in the absence of detectable amounts of bulk host-rock assimilation. High Pd/Pt values have been documented in many world-class magmatic sulfide deposits whose parental magmas have demonstrably experienced crustal contamination. Our model suggests that although anomalous Pd/Pt values may be explained by other mechanisms such as incongruent melting of preexisting sulfide or differences in the diffusivities of the metals within achieving equilibration, the assimilation of graphite or methane may play an important role in the global occurrence of magmatic sulfide ores with elevated Pd/Pt values.</span></p>","language":"English","publisher":"Society of Economic Geologists","doi":"10.5382/econgeo.5165","usgsCitation":"Li, Y., Smith, W.D., Jenkins, M., Yao, Z., and Mungall, J.E., 2025, Assimilation of reduced carbon triggers platinum alloy saturation in mafic and ultramafic magmas: Economic Geology, v. 120, no. 4, p. 1025-1036, https://doi.org/10.5382/econgeo.5165.","productDescription":"12 p.","startPage":"1025","endPage":"1036","ipdsId":"IP-151208","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":491179,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"120","issue":"4","noUsgsAuthors":false,"publicationDate":"2025-06-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Li, Ying Zhou","contributorId":357308,"corporation":false,"usgs":false,"family":"Li","given":"Ying Zhou","affiliations":[{"id":85402,"text":"Carleton University; Saskatchewan Geological Survey","active":true,"usgs":false}],"preferred":false,"id":941157,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smith, William D.","contributorId":335361,"corporation":false,"usgs":false,"family":"Smith","given":"William","email":"","middleInitial":"D.","affiliations":[{"id":17786,"text":"Carleton University","active":true,"usgs":false}],"preferred":false,"id":941158,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jenkins, Michael 0000-0002-4261-409X mjenkins@usgs.gov","orcid":"https://orcid.org/0000-0002-4261-409X","contributorId":172433,"corporation":false,"usgs":true,"family":"Jenkins","given":"Michael","email":"mjenkins@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":941159,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Yao, Zhuosen","contributorId":357309,"corporation":false,"usgs":false,"family":"Yao","given":"Zhuosen","affiliations":[{"id":12433,"text":"China University of Geosciences","active":true,"usgs":false}],"preferred":false,"id":941160,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mungall, James E. 0000-0001-9726-8545","orcid":"https://orcid.org/0000-0001-9726-8545","contributorId":269537,"corporation":false,"usgs":false,"family":"Mungall","given":"James","email":"","middleInitial":"E.","affiliations":[{"id":17786,"text":"Carleton University","active":true,"usgs":false}],"preferred":false,"id":941161,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70268974,"text":"70268974 - 2025 - A generalized deep learning model to detect and classify volcano seismicity","interactions":[],"lastModifiedDate":"2025-07-11T13:50:23.102749","indexId":"70268974","displayToPublicDate":"2025-06-12T08:44:58","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7593,"text":"Volcanica","active":true,"publicationSubtype":{"id":10}},"title":"A generalized deep learning model to detect and classify volcano seismicity","docAbstract":"<p><span>Volcano seismicity is often detected and classified based on its spectral properties. However, the wide variety of volcano seismic signals and increasing amounts of data make accurate, consistent, and efficient detection and classification challenging. Machine learning (ML) has proven very effective at detecting and classifying tectonic seismicity, particularly using Convolutional Neural Networks (CNNs) and leveraging labeled datasets from regional seismic networks. Progress has been made applying ML to volcano seismicity, but efforts have typically been focused on a single volcano and are often hampered by the limited availability of training data. We build on the method of Tan et al. [2024] (</span>10.1029/2024JB029194<span>) to generalize a spectrogram-based CNN termed the VOlcano Infrasound and Seismic Spectrogram Neural Network (</span><code>VOISS-Net</code><span>) to detect and classify volcano seismicity at any volcano. We use a diverse training dataset of over 270,000 spectrograms from multiple volcanoes: Pavlof, Semisopochnoi, Tanaga, Takawangha, and Redoubt volcanoes\\replaced (Alaska, USA); Mt. Etna (Italy); and Kīlauea, Hawai`i (USA). These volcanoes present a wide range of volcano seismic signals, source-receiver distances, and eruption styles. Our generalized&nbsp;</span><code>VOISS-Net</code><span>&nbsp;model achieves an accuracy of 87 % on the test set. We apply this model to continuous data from several volcanoes and eruptions included within and outside our training set, and find that multiple types of tremor, explosions, earthquakes, long-period events, and noise are successfully detected and classified. The model occasionally confuses transient signals such as earthquakes and explosions and misclassifies seismicity not included in the training dataset (e.g. teleseismic earthquakes). We envision the generalized&nbsp;</span><code>VOISS-Net</code><span>&nbsp;model to be applicable in both research and operational volcano monitoring settings.</span></p>","language":"English","publisher":"Presses universitaires de Strasbourg","doi":"10.30909/vol/rjss1878","usgsCitation":"Fee, D., Tan, D., Lyons, J.J., Sciotto, M., Cannata, A., Hotovec-Ellis, A.J., Girona, T., Wech, A., Roman, D., Haney, M.M., and De Angelis, S., 2025, A generalized deep learning model to detect and classify volcano seismicity: Volcanica, v. 8, no. 1, p. 305-323, https://doi.org/10.30909/vol/rjss1878.","productDescription":"19 p.","startPage":"305","endPage":"323","ipdsId":"IP-178152","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":492467,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.30909/vol/rjss1878","text":"Publisher Index Page"},{"id":492124,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","issue":"1","noUsgsAuthors":false,"publicationDate":"2025-06-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Fee, David 0000-0002-0936-9977","orcid":"https://orcid.org/0000-0002-0936-9977","contributorId":267231,"corporation":false,"usgs":false,"family":"Fee","given":"David","affiliations":[{"id":13097,"text":"Geophysical Institute, University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":942772,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tan, Darren 0000-0001-8210-6041","orcid":"https://orcid.org/0000-0001-8210-6041","contributorId":304978,"corporation":false,"usgs":false,"family":"Tan","given":"Darren","email":"","affiliations":[{"id":66199,"text":"Geophysical Institute and Alaska Volcano Observatory, University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":942773,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lyons, John J. 0000-0001-5409-1698 jlyons@usgs.gov","orcid":"https://orcid.org/0000-0001-5409-1698","contributorId":5394,"corporation":false,"usgs":true,"family":"Lyons","given":"John","email":"jlyons@usgs.gov","middleInitial":"J.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"preferred":true,"id":942774,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sciotto, Mariangela","contributorId":357890,"corporation":false,"usgs":false,"family":"Sciotto","given":"Mariangela","affiliations":[{"id":85561,"text":"Istituto Nazionale di Geofisica e Vulcanologia, Osservatorio Etneo – Sezione di Catania, Catania, Italy.","active":true,"usgs":false}],"preferred":false,"id":942775,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cannata, Andrea","contributorId":236652,"corporation":false,"usgs":false,"family":"Cannata","given":"Andrea","email":"","affiliations":[{"id":47495,"text":"Dipartimento di Scienze Biologiche, Geologiche e Ambientali, Universit`a Degli Studi di Catania, Catania, Italy","active":true,"usgs":false}],"preferred":false,"id":942776,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hotovec-Ellis, Alicia J. 0000-0003-1917-0205","orcid":"https://orcid.org/0000-0003-1917-0205","contributorId":211785,"corporation":false,"usgs":true,"family":"Hotovec-Ellis","given":"Alicia","email":"","middleInitial":"J.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":942777,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Girona, Tarsilo","contributorId":229679,"corporation":false,"usgs":false,"family":"Girona","given":"Tarsilo","email":"","affiliations":[{"id":36392,"text":"Jet Propulsion Laboratory","active":true,"usgs":false},{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":true,"id":942778,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Wech, Aaron awech@usgs.gov","contributorId":194832,"corporation":false,"usgs":true,"family":"Wech","given":"Aaron","email":"awech@usgs.gov","affiliations":[],"preferred":true,"id":942792,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Roman, Diana","contributorId":237832,"corporation":false,"usgs":false,"family":"Roman","given":"Diana","affiliations":[{"id":47620,"text":"Dept. of Terrestrial Magnetism, Carnegie Institution for Science, Washington DC 20015","active":true,"usgs":false}],"preferred":false,"id":942779,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Haney, Matthew M. 0000-0003-3317-7884 mhaney@usgs.gov","orcid":"https://orcid.org/0000-0003-3317-7884","contributorId":172948,"corporation":false,"usgs":true,"family":"Haney","given":"Matthew","email":"mhaney@usgs.gov","middleInitial":"M.","affiliations":[{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":942780,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"De Angelis, Silvio","contributorId":172953,"corporation":false,"usgs":false,"family":"De Angelis","given":"Silvio","affiliations":[{"id":27128,"text":"Univ. of Liverpool","active":true,"usgs":false}],"preferred":false,"id":942781,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}}
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