{"pageNumber":"7","pageRowStart":"150","pageSize":"25","recordCount":184769,"records":[{"id":70274216,"text":"70274216 - 2026 - Groundwater drought in the United States: Spatial and temporal variability","interactions":[],"lastModifiedDate":"2026-03-13T15:11:23.354627","indexId":"70274216","displayToPublicDate":"2026-03-11T10:03:16","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Groundwater drought in the United States: Spatial and temporal variability","docAbstract":"<p><span>Many communities and ecosystems in the United States that are dependent on groundwater are potentially adversely affected by groundwater drought. We computed yearly groundwater-drought metrics and mean groundwater levels at well locations across the conterminous United States (CONUS), using data from wells and remotely sensed and modeled Gravity Recovery and Climate Experiment Drought Monitor Data Assimilation (GRACE-DADM). We also modeled the probability of low or high human impact at each well location. The spatial distribution of groundwater-drought duration and severity from 2001 to 2020 for 1,510 wells shows longer maximum duration and higher maximum severity events in drier regions like the Southwest than in wetter regions like the Northeast. Based on 613 wells in CONUS from 1981 to 2020, there are many significant decreases in drought duration and severity in the Northeast and many significant increases in annual-mean groundwater levels. In contrast, there are many significant increases in drought metrics and decreases in mean water levels in parts of the Southeast. There are major differences in trends from 2001 to 2020 between well-based and GRACE-DADM-based groundwater metrics in some CONUS regions and a very low correlation between trends at individual locations across CONUS. A potential reason for this disparity is the low GRACE-DADM resolution (∼12&nbsp;km) and the potential for a large amount of groundwater variation at the local scale. Also, GRACE-DADM represents shallow, unconfined aquifers which may not match the screened interval of the monitoring wells we evaluated. Large spatial gaps in long-term, high frequency, and quality-assured groundwater-well monitoring data present a challenge for understanding groundwater-drought variability across CONUS. Remote sensing tools such as GRACE can help but cannot fully replace well monitoring, as highlighted by our study results. Substantially more long-term monitoring wells would more accurately represent groundwater-drought trends and spatial variability across CONUS, particularly in western regions.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2026.135180","usgsCitation":"Hodgkins, G., Simeone, C., Lombard, M.A., Caldwell, T., Hammond, J., Wieczorek, M., and Dudley, R., 2026, Groundwater drought in the United States: Spatial and temporal variability: Journal of Hydrology, v. 671, 135180, 18 p., https://doi.org/10.1016/j.jhydrol.2026.135180.","productDescription":"135180, 18 p.","ipdsId":"IP-163725","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":501147,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"conterminous United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      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Water Science Center","active":true,"usgs":true}],"preferred":true,"id":957072,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Simeone, Caelan 0000-0003-3263-6452","orcid":"https://orcid.org/0000-0003-3263-6452","contributorId":221008,"corporation":false,"usgs":true,"family":"Simeone","given":"Caelan","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":957073,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lombard, Melissa A. 0000-0001-5924-6556 mlombard@usgs.gov","orcid":"https://orcid.org/0000-0001-5924-6556","contributorId":198254,"corporation":false,"usgs":true,"family":"Lombard","given":"Melissa","email":"mlombard@usgs.gov","middleInitial":"A.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":957074,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Caldwell, Todd 0000-0003-4068-0648","orcid":"https://orcid.org/0000-0003-4068-0648","contributorId":217924,"corporation":false,"usgs":true,"family":"Caldwell","given":"Todd","email":"","affiliations":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"preferred":true,"id":957075,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hammond, John C. 0000-0002-4935-0736","orcid":"https://orcid.org/0000-0002-4935-0736","contributorId":223108,"corporation":false,"usgs":true,"family":"Hammond","given":"John C.","affiliations":[{"id":41514,"text":"Maryland-Delaware-District of Columbia  Water Science Center","active":true,"usgs":true}],"preferred":true,"id":957076,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wieczorek, Michael 0000-0003-0999-5457","orcid":"https://orcid.org/0000-0003-0999-5457","contributorId":207911,"corporation":false,"usgs":true,"family":"Wieczorek","given":"Michael","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":957077,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Dudley, Robert W. 0000-0002-0934-0568","orcid":"https://orcid.org/0000-0002-0934-0568","contributorId":220211,"corporation":false,"usgs":true,"family":"Dudley","given":"Robert W.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":957078,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70274211,"text":"70274211 - 2026 - Small-volume tephra deposits of the May 1924 explosions from Halemaʻumaʻu, Kīlauea volcano, and their origin","interactions":[],"lastModifiedDate":"2026-03-13T14:29:50.599041","indexId":"70274211","displayToPublicDate":"2026-03-11T09:20:41","publicationYear":"2026","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}},"title":"Small-volume tephra deposits of the May 1924 explosions from Halemaʻumaʻu, Kīlauea volcano, and their origin","docAbstract":"<div id=\"sp0085\" class=\"u-margin-s-bottom\">More than 50 explosive eruptions occurred from Halemaʻumaʻu at Kīlauea volcano over 17&nbsp;days from May 11 to 27, 1924. Ballistics weighing as much as 14,000&nbsp;kg were ejected and most landed within 2&nbsp;km of the vent. Fine ash made up a major component of the tephra and was dispersed tens of kilometers downwind. Draining of the Halemaʻumaʻu lava lake occurred in late February 1924, with the crater floor eventually subsiding by a further ∼70&nbsp;m (to ∼180&nbsp;m below the crater rim) by the time the first explosions took place during the night of May 10–11. The largest explosions occurred on May 17–18 and smaller explosions continued until May 27, at which point Halemaʻumaʻu had more than doubled in width and depth. The explosions generated plumes reaching up to ∼10&nbsp;km high with ballistics ejected up to 2&nbsp;km from the crater.</div><div id=\"sp0090\" class=\"u-margin-s-bottom\">Almost 100&nbsp;years later, we investigate and characterize the preserved tephra deposits within ∼3&nbsp;km of the 1924 crater rim. Grain size and shape analyses were performed on 202 samples collected from 34 tephra profiles using dynamic image analysis, with a subset of layers from nine tephra profiles used for componentry (200 grains per layer in the 0.5–1&nbsp;mm size fraction). Additionally, we characterize the average diameters (using the five largest clasts) at 216 locations and measure the average diameters of 2291 ballistics (largest per ∼100&nbsp;m<sup>2</sup><span>&nbsp;</span>area). Physical descriptions from fieldwork and grain size distributions were used to subdivide the tephra layers into five lithofacies: coarse homogeneous, fine homogenous, red ash, accretionary lapilli-bearing, and finely laminated. Grain size versus shape data show a range of values that demonstrate most grains are dense, smooth, and equant, in alignment with lithic clasts dominating the tephra componentry. The fine grained and accretionary lapilli-bearing nature of some of these lithofacies confirms that water influenced the style of the explosions. However, we also note juvenile clasts within many of the tephra layers, indicating that many of the layers were formed during phreatomagmatic explosions (sensu stricto), despite the eruptive mechanism being dominantly phreatic. Juvenile clasts are more abundant higher in the tephra profiles, suggesting that juvenile magma was more involved later in the explosive sequence. Thermal and hydrologic modeling indicate that groundwater inflow into a short-lived, small-diameter volcanic conduit (10-m to 120-m-diameter used for modeling) during the 78–85 days preceding the first explosion provides a physically plausible mechanism for this eruptive sequence.</div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jvolgeores.2026.108589","usgsCitation":"Downs, D.T., Schmith, J., Chang, J., Lynn, K.J., Swanson, D., Gaddis, B., and Flinders, A.F., 2026, Small-volume tephra deposits of the May 1924 explosions from Halemaʻumaʻu, Kīlauea volcano, and their origin: Journal of Volcanology and Geothermal Research, v. 473, 108589, 21 p., https://doi.org/10.1016/j.jvolgeores.2026.108589.","productDescription":"108589, 21 p.","ipdsId":"IP-169312","costCenters":[{"id":336,"text":"Hawaiian Volcano Observatory","active":false,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":501132,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Halemaʻumaʻu, Kīlauea volcano","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -155.32093940239616,\n              19.462043698480926\n            ],\n            [\n              -155.32093940239616,\n              19.355974406399667\n            ],\n            [\n              -155.22000056879196,\n              19.355974406399667\n            ],\n            [\n              -155.22000056879196,\n              19.462043698480926\n            ],\n            [\n              -155.32093940239616,\n              19.462043698480926\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"473","noUsgsAuthors":false,"publicationDate":"2026-03-11","publicationStatus":"PW","contributors":{"authors":[{"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":957036,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schmith, Johanne 0000-0002-0912-7441","orcid":"https://orcid.org/0000-0002-0912-7441","contributorId":334956,"corporation":false,"usgs":true,"family":"Schmith","given":"Johanne","affiliations":[{"id":80292,"text":"Hawaiian Volcano Observatory","active":true,"usgs":false}],"preferred":true,"id":957037,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chang, Julie 0000-0002-3330-062X","orcid":"https://orcid.org/0000-0002-3330-062X","contributorId":304400,"corporation":false,"usgs":true,"family":"Chang","given":"Julie","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":957038,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lynn, Kendra J. 0000-0001-7886-4376","orcid":"https://orcid.org/0000-0001-7886-4376","contributorId":290327,"corporation":false,"usgs":true,"family":"Lynn","given":"Kendra","email":"","middleInitial":"J.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":957039,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Swanson, Don 0000-0002-1680-3591 donswan@usgs.gov","orcid":"https://orcid.org/0000-0002-1680-3591","contributorId":168817,"corporation":false,"usgs":true,"family":"Swanson","given":"Don","email":"donswan@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":957040,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gaddis, Ben 0000-0001-7280-353X","orcid":"https://orcid.org/0000-0001-7280-353X","contributorId":203453,"corporation":false,"usgs":true,"family":"Gaddis","given":"Ben","email":"","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":957041,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Flinders, Ashton F. 0000-0003-2483-4635","orcid":"https://orcid.org/0000-0003-2483-4635","contributorId":271052,"corporation":false,"usgs":true,"family":"Flinders","given":"Ashton","email":"","middleInitial":"F.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":957042,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70274538,"text":"70274538 - 2026 - Density dependence and habitat selection affect overwintering abundance of monarch butterflies at regional and site scales in California","interactions":[],"lastModifiedDate":"2026-04-20T15:53:44.921013","indexId":"70274538","displayToPublicDate":"2026-03-10T16:01:47","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5803,"text":"Conservation Science and Practice","active":true,"publicationSubtype":{"id":10}},"title":"Density dependence and habitat selection affect overwintering abundance of monarch butterflies at regional and site scales in California","docAbstract":"<p><span>The monarch butterfly (</span><i>Danaus plexippus</i><span>) is a species of iconic cultural interest. Thanks to annual overwintering monarch counts at hundreds of locations in coastal California, we are able to track fluctuations with high temporal and spatial resolution. Between 1997 and 2024, monarch populations at overwintering sites in the western United States experienced severe dips, at times (2018–2020, 2023–2024) giving the appearance of a population collapse. From 2018 to present, the Pismo State Beach Overwintering Monarch Grove has conducted multiple counts during overwintering and geolocated counts of individual monarch clusters to specific trees within the site. This study determined how annual monarch population variability is influenced by both climate and prior year population density at the state, region, and overwintering-site scale. Furthermore, through a machine-learning process, we investigated how overwintering site configuration and structure drive monarch winter space-use dynamics within the Pismo Beach site. Our approach found monarchs exhibit a preference for specific overwintering sites in California, and that 64% of annual variability of counts across sites can be explained by climate and density dependence, with density dependence explaining 50% of total variability. Within the site we found very little regional climate effect, but individual trees, tree size, distance to boundary, and the amount of shade were all strong indicators of monarch presence. Additionally, only 11 out of 320 trees at the Pismo Beach site accounted for 83.6% of all counts over 6 years, highlighting how monarchs use specific trees and how tree structure may create preferred microclimates for clustering.</span></p>","language":"English","publisher":"Society for Conservation Biology","doi":"10.1111/csp2.70253","usgsCitation":"Ibsen, P.C., Ancona, Z.H., Pelton, E., Little, S., and Diffendorfer, J., 2026, Density dependence and habitat selection affect overwintering abundance of monarch butterflies at regional and site scales in California: Conservation Science and Practice, v. 8, no. 4, e70253, 16 p., https://doi.org/10.1111/csp2.70253.","productDescription":"e70253, 16 p.","ipdsId":"IP-172212","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":501884,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":502079,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/csp2.70253","text":"Publisher Index Page"}],"country":"United States","state":"California","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -123,\n              38\n            ],\n            [\n              -123,\n              34\n            ],\n            [\n              -119.5,\n              34\n            ],\n            [\n              -119.5,\n              38\n            ],\n            [\n              -123,\n              38\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"8","issue":"4","noUsgsAuthors":false,"publicationDate":"2026-03-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Ibsen, Peter Christian 0000-0002-3436-9100","orcid":"https://orcid.org/0000-0002-3436-9100","contributorId":260735,"corporation":false,"usgs":true,"family":"Ibsen","given":"Peter","email":"","middleInitial":"Christian","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":958161,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ancona, Zachary H. 0000-0001-5430-0218 zancona@usgs.gov","orcid":"https://orcid.org/0000-0001-5430-0218","contributorId":5578,"corporation":false,"usgs":true,"family":"Ancona","given":"Zachary","email":"zancona@usgs.gov","middleInitial":"H.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":958162,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pelton, Emma","contributorId":357706,"corporation":false,"usgs":false,"family":"Pelton","given":"Emma","affiliations":[{"id":34267,"text":"The Xerces Society for Invertebrate Conservation","active":true,"usgs":false}],"preferred":false,"id":958163,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Little, Stephanie","contributorId":368952,"corporation":false,"usgs":false,"family":"Little","given":"Stephanie","affiliations":[{"id":35321,"text":"California Department of Parks and Recreation","active":true,"usgs":false}],"preferred":false,"id":958164,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Diffendorfer, James E. 0000-0003-1093-6948 jediffendorfer@usgs.gov","orcid":"https://orcid.org/0000-0003-1093-6948","contributorId":3208,"corporation":false,"usgs":true,"family":"Diffendorfer","given":"James E.","email":"jediffendorfer@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":958165,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70274236,"text":"70274236 - 2026 - Accumulation of per- and polyfluoroalkyl substances (PFAS) and their association with immune parameters in nestling ospreys (Pandion haliaetus) from Chesapeake and Delaware Bays, USA","interactions":[],"lastModifiedDate":"2026-03-23T12:53:32.533122","indexId":"70274236","displayToPublicDate":"2026-03-10T14:19:03","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1571,"text":"Environmental Toxicology and Chemistry","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Accumulation of per- and polyfluoroalkyl substances (PFAS) and their association with immune parameters in nestling ospreys (<i>Pandion haliaetus</i>) from Chesapeake and Delaware Bays, USA","title":"Accumulation of per- and polyfluoroalkyl substances (PFAS) and their association with immune parameters in nestling ospreys (Pandion haliaetus) from Chesapeake and Delaware Bays, USA","docAbstract":"<p><span>Per- and polyfluoroalkyl substances (PFAS) are a class of widespread, environmentally persistent compounds that pose a potential threat to wildlife and human health. Despite recent efforts to reduce the use of long-chain PFAS in industrial practices and commercial/consumer products, the persistence and solubility of PFAS have led to their detection in wildlife on a global scale. Osprey (</span><i>Pandion haliaetus</i><span>) have long been used as a sentinel species with an extensive history of serving as an effective bioindicator of contamination. Here we report on a large-scale evaluation of PFAS and potential health effects in osprey from the Chesapeake and Delaware Bays, USA. In 2011 and 2015, we collected plasma samples from osprey nestlings throughout the Chesapeake and Delaware Bay watersheds. We quantified 40 PFAS congeners in osprey plasma via liquid chromatography-mass spectrometry and analyzed plasma for indicators of immune and thyroid function, and plasma biochemistry. In all birds, perfluorooctanesulfonic acid (PFOS) was the most commonly detected PFAS, followed by perfluoroundecanoic acid, (PFUnA) and perfluorodecanoic acid (PFDA). In nestling plasma from Chesapeake Bay, PFOS tended to be a higher average contributor to PFAS profiles compared to samples from Delaware Bay. In contrast, long-chain perfluoroalkyl carboxylic acids (PFCAs) such as PFUnA and PFDA comprised larger percentages of total PFAS in osprey plasma from Delaware Bay relative to Chesapeake Bay. While some PFAS concentrations were associated with plasma health indicators, the proportion of variation explained was low. Overall, our study provides a more thorough understanding of PFAS presence in the Chesapeake and Delaware Bays and is one of the first to examine whether PFAS exposure is associated with adverse health effects in wildlife.</span></p>","language":"English","publisher":"Oxford Academic","doi":"10.1093/etojnl/vgag055","usgsCitation":"Karouna-Renier, N., Haskins, D., Schultz, S.L., Akresh, M., and Rattner, B., 2026, Accumulation of per- and polyfluoroalkyl substances (PFAS) and their association with immune parameters in nestling ospreys (Pandion haliaetus) from Chesapeake and Delaware Bays, USA: Environmental Toxicology and Chemistry, https://doi.org/10.1093/etojnl/vgag055.","ipdsId":"IP-183725","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":501383,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/ja/70274236/images"},{"id":501382,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/ja/70274236/70274236.XML"},{"id":501381,"rank":2,"type":{"id":42,"text":"Open Access USGS Document"},"url":"https://pubs.usgs.gov/publication/70274236/full"},{"id":501230,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Chesapeake and Delaware Bays","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -74.61761223029669,\n              39.86211116682409\n            ],\n            [\n              -76.93592404163553,\n              39.86211116682409\n            ],\n            [\n              -76.93592404163553,\n              36.61322897844552\n            ],\n            [\n              -74.61761223029669,\n              36.61322897844552\n            ],\n            [\n              -74.61761223029669,\n              39.86211116682409\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","edition":"Online First","noUsgsAuthors":false,"publicationDate":"2026-03-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Karouna-Renier, Natalie 0000-0001-7127-033X nkarouna@usgs.gov","orcid":"https://orcid.org/0000-0001-7127-033X","contributorId":200983,"corporation":false,"usgs":true,"family":"Karouna-Renier","given":"Natalie","email":"nkarouna@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":957120,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Haskins, David Lee 0000-0002-6692-3225","orcid":"https://orcid.org/0000-0002-6692-3225","contributorId":357996,"corporation":false,"usgs":true,"family":"Haskins","given":"David Lee","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":957121,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schultz, Sandra L. 0000-0003-3394-2857 sschultz@usgs.gov","orcid":"https://orcid.org/0000-0003-3394-2857","contributorId":5966,"corporation":false,"usgs":true,"family":"Schultz","given":"Sandra","email":"sschultz@usgs.gov","middleInitial":"L.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":957122,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Akresh, Michael E.","contributorId":355344,"corporation":false,"usgs":false,"family":"Akresh","given":"Michael E.","affiliations":[{"id":83385,"text":"Antioch University","active":true,"usgs":false}],"preferred":false,"id":957123,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rattner, Barnett 0000-0003-3676-2843 brattner@usgs.gov","orcid":"https://orcid.org/0000-0003-3676-2843","contributorId":221814,"corporation":false,"usgs":true,"family":"Rattner","given":"Barnett","email":"brattner@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":957124,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70274632,"text":"70274632 - 2026 - Hydrologic variability drives environmental and geospatial relationships in Smallmouth Bass (Micropterus dolomieu) distribution","interactions":[],"lastModifiedDate":"2026-04-02T18:44:26.919721","indexId":"70274632","displayToPublicDate":"2026-03-10T11:32:48","publicationYear":"2026","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}},"displayTitle":"Hydrologic variability drives environmental and geospatial relationships in Smallmouth Bass (<i>Micropterus dolomieu</i>) distribution","title":"Hydrologic variability drives environmental and geospatial relationships in Smallmouth Bass (Micropterus dolomieu) distribution","docAbstract":"<p><span id=\"_mce_caret\" data-mce-bogus=\"1\" data-mce-type=\"format-caret\"><span>Hydrologic variation is a primary driver of stream ecosystems. Changing hydrology can lead to assemblage shifts and alterations in suitable habitat for freshwater species. As climate change is predicted to alter flow patterns in addition to increasing water temperatures, insight into relationships between species occupancy, hydrology, and temperature is critical for understanding current and future distributions. We examined how hydrologic variability, temperature, and other environmental variables interact to influence&nbsp;</span><i>Micropterus dolomieu</i><span>&nbsp;(Smallmouth Bass) occurrence. We used Spatial Stream Network models, allowing for the incorporation of spatial autocorrelation along streams' unique dendritic network, to examine Smallmouth Bass occupancy across a range of hydrologic variation in the Ozark-Ouachita Interior Highlands, USA. Hydrologic variation was the main driver of Smallmouth Bass occurrence, with occurrence more likely in groundwater streams with low hydrologic variation and high flow permanence. For groundwater streams, occurrence was positively associated with summer stream temperature and negatively associated with annual stream temperature. As variation increased, more variables showed significant relationships with occurrence. Distance metrics were important for all models, however as hydrologic disturbance increased, flow connected distance played a lesser role and stream distance played a greater role. Hydrologic variability was the overarching determinant of Smallmouth Bass occurrence and strongly influenced the predictive importance of environmental variables and geospatial relationships. Greater hydrologic variability resulted in stronger statistical relationships between occurrence and environmental variables and an increased importance of system connectivity. As climate change alters hydrologic processes and streams become more variable, understanding and accounting for these shifting relationships is essential.</span></span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2026.181562","usgsCitation":"Sorensen, S.F., Fox, J.T., and Magoulick, D.D., 2026, Hydrologic variability drives environmental and geospatial relationships in Smallmouth Bass (Micropterus dolomieu) distribution: Science of the Total Environment, v. 1025, 181562, 9 p., https://doi.org/10.1016/j.scitotenv.2026.181562.","productDescription":"181562, 9 p.","ipdsId":"IP-176491","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":502098,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2026.181562","text":"Publisher Index Page"},{"id":502032,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arkansas, Kansas, Missouri, Oklahoma","otherGeospatial":"Ozark-Ouachita Interior Highlands","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -95.06835076729865,\n              37.54392591075137\n            ],\n            [\n              -95.58753725694291,\n              35.616131979244244\n            ],\n            [\n              -96.86430792379102,\n              34.30485408838467\n            ],\n            [\n              -95.13839254168458,\n              34.13182914589751\n            ],\n            [\n              -93.02844126052034,\n              33.84485206480821\n            ],\n            [\n              -91.20526644252189,\n              35.93662462412837\n            ],\n            [\n              -90.46426221649432,\n              38.03635872039271\n            ],\n            [\n              -95.06835076729865,\n              37.54392591075137\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"1025","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Sorensen, Sarah F.","contributorId":369126,"corporation":false,"usgs":false,"family":"Sorensen","given":"Sarah","middleInitial":"F.","affiliations":[{"id":6623,"text":"University of Arkansas","active":true,"usgs":false}],"preferred":false,"id":958495,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fox, J. Tyler","contributorId":369127,"corporation":false,"usgs":false,"family":"Fox","given":"J.","middleInitial":"Tyler","affiliations":[{"id":6623,"text":"University of Arkansas","active":true,"usgs":false}],"preferred":false,"id":958496,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Magoulick, Daniel D. 0000-0001-9665-5957 danmag@usgs.gov","orcid":"https://orcid.org/0000-0001-9665-5957","contributorId":2513,"corporation":false,"usgs":true,"family":"Magoulick","given":"Daniel","email":"danmag@usgs.gov","middleInitial":"D.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":958497,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70274596,"text":"70274596 - 2026 - Continuous measurements reveal wind and temperature affect orphan well methane emissions on the Kevin-Sunburst Dome, Montana","interactions":[],"lastModifiedDate":"2026-04-01T18:05:24.62617","indexId":"70274596","displayToPublicDate":"2026-03-10T10:59:16","publicationYear":"2026","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":"Continuous measurements reveal wind and temperature affect orphan well methane emissions on the Kevin-Sunburst Dome, Montana","docAbstract":"<p><span id=\"_mce_caret\" data-mce-bogus=\"1\" data-mce-type=\"format-caret\"><span>Fifteen leaking orphan wells on the Kevin-Sunburst Dome in northern Montana had emission rates that were affected by surface winds and diurnal temperature swings based on continuous monitoring data. Some wells showed correlating spikes in emissions when temperatures changed or wind speed increased while others demonstrated independent flow behavior despite being drilled into the same reservoir and located only a few hundred meters apart. Time-weighted mean methane emission rates ranged from non-detectable levels up to 2.7&nbsp;kg/h in their as-discovered conditions, with leaking wells averaging 211&nbsp;g/h. Emissions were measured continuously for up to 452&nbsp;h per well during monitoring, revealing that leak rates can fluctuate by an order of magnitude within hours. Fluctuations in emission rates often synchronized between wells with overlapping emission measurement intervals, suggesting weather conditions, such as temperature and wind, affect emission rates (up to a factor of 4) with the most relevant factor being the effect of wind on wells with open holes. Additionally, this study presents the first methane emissions measured from an orphan well in two distinct conditions: as initially discovered (closed leaking valve, 2.7&nbsp;kg/h) and again under unrestricted flow conditions (open valve, 11.8&nbsp;kg/h), illustrating the maximum unobstructed leak rate and quantifying the constraints restricted leaking wells can have on emissions compared to open holes.</span></span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2026.181577","usgsCitation":"Gianoutsos, N.J., Haase, K.B., Birdwell, J.E., Hofmann, M.H., and Shuck, C.E., 2026, Continuous measurements reveal wind and temperature affect orphan well methane emissions on the Kevin-Sunburst Dome, Montana: Science of the Total Environment, v. 1020, 181577, 12 p., https://doi.org/10.1016/j.scitotenv.2026.181577.","productDescription":"181577, 12 p.","ipdsId":"IP-173165","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":502054,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2026.181577","text":"Publisher Index Page"},{"id":501959,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana","otherGeospatial":"Kevin-Sunburst Dome","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -112.08584178503881,\n              48.942193767762035\n            ],\n            [\n              -112.08584178503881,\n              47.38524088668447\n            ],\n            [\n              -109.50509067788585,\n              47.38524088668447\n            ],\n            [\n              -109.50509067788585,\n              48.942193767762035\n            ],\n            [\n              -112.08584178503881,\n              48.942193767762035\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"1020","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Gianoutsos, Nicholas J. 0000-0002-6510-6549 ngianoutsos@usgs.gov","orcid":"https://orcid.org/0000-0002-6510-6549","contributorId":3607,"corporation":false,"usgs":true,"family":"Gianoutsos","given":"Nicholas","email":"ngianoutsos@usgs.gov","middleInitial":"J.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":958461,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Haase, Karl B. 0000-0002-6897-6494 khaase@usgs.gov","orcid":"https://orcid.org/0000-0002-6897-6494","contributorId":205943,"corporation":false,"usgs":true,"family":"Haase","given":"Karl","email":"khaase@usgs.gov","middleInitial":"B.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":958462,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Birdwell, Justin E. 0000-0001-8263-1452 jbirdwell@usgs.gov","orcid":"https://orcid.org/0000-0001-8263-1452","contributorId":3302,"corporation":false,"usgs":true,"family":"Birdwell","given":"Justin","email":"jbirdwell@usgs.gov","middleInitial":"E.","affiliations":[{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":569,"text":"Southwest Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":958463,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hofmann, Michael H.","contributorId":369106,"corporation":false,"usgs":false,"family":"Hofmann","given":"Michael","middleInitial":"H.","affiliations":[{"id":36523,"text":"University of Montana","active":true,"usgs":false}],"preferred":false,"id":958464,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Shuck, Curtis E.","contributorId":369107,"corporation":false,"usgs":false,"family":"Shuck","given":"Curtis","middleInitial":"E.","affiliations":[{"id":87723,"text":"Well Done Foundation","active":true,"usgs":false}],"preferred":false,"id":958465,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70274546,"text":"70274546 - 2026 - Scenarios and strategies for future-proofing ecosystem management under climatic novelty","interactions":[],"lastModifiedDate":"2026-04-01T22:08:35.698045","indexId":"70274546","displayToPublicDate":"2026-03-09T15:01:30","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1321,"text":"Conservation Biology","active":true,"publicationSubtype":{"id":10}},"title":"Scenarios and strategies for future-proofing ecosystem management under climatic novelty","docAbstract":"<p><span id=\"_mce_caret\" data-mce-bogus=\"1\" data-mce-type=\"format-caret\"><span>Climate change is driving unprecedented declines in dominant, habitat-forming foundation species across marine and terrestrial ecosystems globally. As climatic novelty becomes the norm, ecosystem reassembly will become increasingly common. Predicting and understanding these transitions, and their implications for future ecosystem functioning, is essential for designing effective forward-looking management strategies. We explored 3 scenarios that describe a range of ecosystem reassembly trajectories following declines in previously dominant habitat-forming taxa: compensation, in which functionally similar subdominant or immigrating taxa maintain ecosystem structure and function; decline, in which no compensation occurs leading to loss of ecosystem structure and function; and transformation, in which the ecosystem present historically can no longer persist and shifts into a fundamentally different ecosystem type with distinct structure and function. This range of potential outcomes highlights the urgent need to assess the ecological feasibility and functional implications of potential management actions. Scientists and managers can work together to quantify local-scale climatic novelty and ecosystem resilience&nbsp;to better predict&nbsp;the most likely reassembly trajectories and identify management interventions that will optimize ecosystem function. This approach would allow for more proactive planning to support persistence of ecosystem structure and function, helping to future-proof ecosystem management in a rapidly changing world.</span></span></p>","language":"English","publisher":"Society for Conservation Biology","doi":"10.1111/cobi.70250","usgsCitation":"Toth, L.T., Borer, E.T., Burkepile, D.E., Dudney, J., Lemoine, N.P., Renzi, J.J., Smith, K.E., Courtney, T.A., Goeking, S.A., Hammond, W.M., Hoover, D.L., MacFayden, S., Osland, M.J., Townsend, J.E., and Fidler, R.Y., 2026, Scenarios and strategies for future-proofing ecosystem management under climatic novelty: Conservation Biology, e70250, 12 p., https://doi.org/10.1111/cobi.70250.","productDescription":"e70250, 12 p.","ipdsId":"IP-176414","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":502061,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/cobi.70250","text":"Publisher Index Page"},{"id":501973,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"edition":"Online First","noUsgsAuthors":false,"publicationDate":"2026-03-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Toth, Lauren T. 0000-0002-2568-802X ltoth@usgs.gov","orcid":"https://orcid.org/0000-0002-2568-802X","contributorId":181748,"corporation":false,"usgs":true,"family":"Toth","given":"Lauren","email":"ltoth@usgs.gov","middleInitial":"T.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":958224,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Borer, Elizabeth T.","contributorId":368991,"corporation":false,"usgs":false,"family":"Borer","given":"Elizabeth","middleInitial":"T.","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":958225,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Burkepile, Deron E.","contributorId":368992,"corporation":false,"usgs":false,"family":"Burkepile","given":"Deron","middleInitial":"E.","affiliations":[{"id":16936,"text":"University of California Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":958226,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dudney, Joan","contributorId":223741,"corporation":false,"usgs":false,"family":"Dudney","given":"Joan","affiliations":[{"id":40762,"text":"University of California, Berkley","active":true,"usgs":false}],"preferred":false,"id":958227,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lemoine, Nathan P.","contributorId":368993,"corporation":false,"usgs":false,"family":"Lemoine","given":"Nathan","middleInitial":"P.","affiliations":[{"id":64527,"text":"Marquette University","active":true,"usgs":false}],"preferred":false,"id":958228,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Renzi, Julianna J.","contributorId":368994,"corporation":false,"usgs":false,"family":"Renzi","given":"Julianna","middleInitial":"J.","affiliations":[{"id":16936,"text":"University of California Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":958229,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Smith, Kathryn E.L. 0000-0002-7521-7875 kelsmith@usgs.gov","orcid":"https://orcid.org/0000-0002-7521-7875","contributorId":173264,"corporation":false,"usgs":true,"family":"Smith","given":"Kathryn","email":"kelsmith@usgs.gov","middleInitial":"E.L.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":958230,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Courtney, Travis A.","contributorId":368995,"corporation":false,"usgs":false,"family":"Courtney","given":"Travis","middleInitial":"A.","affiliations":[{"id":34129,"text":"University of Puerto Rico Mayaguez","active":true,"usgs":false}],"preferred":false,"id":958231,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Goeking, Sara A.","contributorId":368996,"corporation":false,"usgs":false,"family":"Goeking","given":"Sara","middleInitial":"A.","affiliations":[{"id":37389,"text":"U.S. Forest Service","active":true,"usgs":false}],"preferred":false,"id":958232,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Hammond, William M.","contributorId":368997,"corporation":false,"usgs":false,"family":"Hammond","given":"William","middleInitial":"M.","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":958233,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Hoover, David L.","contributorId":368998,"corporation":false,"usgs":false,"family":"Hoover","given":"David","middleInitial":"L.","affiliations":[{"id":36658,"text":"U.S. Department of Agriculture","active":true,"usgs":false}],"preferred":false,"id":958234,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"MacFayden, Sandra","contributorId":368999,"corporation":false,"usgs":false,"family":"MacFayden","given":"Sandra","affiliations":[{"id":39919,"text":"Stellenbosch University","active":true,"usgs":false}],"preferred":false,"id":958235,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Osland, Michael J. 0000-0001-9902-8692","orcid":"https://orcid.org/0000-0001-9902-8692","contributorId":206443,"corporation":false,"usgs":true,"family":"Osland","given":"Michael","middleInitial":"J.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":958236,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Townsend, Joseph E.","contributorId":369000,"corporation":false,"usgs":false,"family":"Townsend","given":"Joseph","middleInitial":"E.","affiliations":[{"id":34129,"text":"University of Puerto Rico Mayaguez","active":true,"usgs":false}],"preferred":false,"id":958237,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Fidler, Robert Young 0000-0001-8796-9161","orcid":"https://orcid.org/0000-0001-8796-9161","contributorId":369001,"corporation":false,"usgs":true,"family":"Fidler","given":"Robert","middleInitial":"Young","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":958238,"contributorType":{"id":1,"text":"Authors"},"rank":15}]}}
,{"id":70274195,"text":"sim3545 - 2026 - Water use permits as of July 2024 and reported water use near the North Unit of Theodore Roosevelt National Park, North Dakota, 1980–2023","interactions":[],"lastModifiedDate":"2026-03-13T16:57:02.210512","indexId":"sim3545","displayToPublicDate":"2026-03-09T11:44:43","publicationYear":"2026","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3545","displayTitle":"Water Use Permits as of July 2024 and Reported Water Use Near the North Unit of Theodore Roosevelt National Park, North Dakota, 1980–2023","title":"Water use permits as of July 2024 and reported water use near the North Unit of Theodore Roosevelt National Park, North Dakota, 1980–2023","docAbstract":"<p>Starting in the early 2000s, increasing oil and gas development in western North Dakota created a need for additional water resources from surface-water and groundwater sources near the North Unit of Theodore Roosevelt National Park. To summarize the use of water in that area, the U.S. Geological Survey, in cooperation with the National Park Service, developed a map of surface-water and groundwater resources, aquifers, and water-use diversions, and plotted water-use trends from 1980 to 2023. Reported water used from permits in the map area has more than doubled since 2020, increasing from about 750 acre-feet in 2020 to about 2,300 acre-feet in 2022 and 2,000 acre-feet in 2023. Surface water provided the primary source of reported water used for the study period with an average of about 410 acre-feet per year from 1980 through 2017 and about 1,330 acre-feet per year from 2018 through 2023. After 2011, groundwater sourced from the Little Missouri River, Tobacco Garden Creek, Fox Hills, Fort Union, and Dakota aquifers became a larger portion of total annual reported water use from permits in the map area. From 1980 through 2015, water use for irrigation averaged 86 percent of the total annual reported surface-water and groundwater use in the map area. Starting in 2011, however, industrial uses became a proportionally larger total use of water, and in 2015, became the highest reported volume of water use in the map area. From 2011 to 2023, industrial use designated for water depots increased from 50 acre-feet to about 1,370 acre-feet, accounting for about 70 percent of total reported water use in the map area in 2023.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3545","collaboration":"Prepared in cooperation with the National Park Service","usgsCitation":"Anderson, T.M., and Medler, C.J., 2026, Water use permits as of July 2024 and reported water use near the North Unit of Theodore Roosevelt National Park, North Dakota, 1980–2023: U.S. Geological Survey Scientific Investigations Map 3545, 1 p., scale 1:75,000, https://doi.org/10.3133/sim3545.","productDescription":"1 Sheet: 51.96 x 32.00 inches","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-180137","costCenters":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":501164,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_119300.htm","linkFileType":{"id":5,"text":"html"}},{"id":500796,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3545/sim3545.pdf","text":"Report","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3545"},{"id":500795,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3545/coverthb.jpg"}],"country":"United States","state":"North Dakota","otherGeospatial":"North Unit of Theodore Roosevelt National Park","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -103.68187232257335,\n              47.72042516981429\n            ],\n            [\n              -103.68187232257335,\n              47.454023726420644\n            ],\n            [\n              -103.19621849492077,\n              47.454023726420644\n            ],\n            [\n              -103.19621849492077,\n              47.72042516981429\n            ],\n            [\n              -103.68187232257335,\n              47.72042516981429\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","contact":"<p>Director,&nbsp;<a href=\"https://www.usgs.gov/centers/dakota-water\" data-mce-href=\"https://www.usgs.gov/centers/dakota-water\">Dakota Water Science Center</a><br>U.S. Geological Survey<br>821 East Interstate Avenue, Bismarck, ND 58503<br>1608 Mountain View Road, Rapid City, SD 57702</p><p><a href=\"https://pubs.usgs.gov/contact\" data-mce-href=\"../contact\">Contact Pubs Warehouse</a></p>","tableOfContents":"<ul><li>Plain Language Summary</li><li>Abstract</li><li>Introduction</li><li>Hydrogeologic Setting</li><li>Sources of Water</li><li>Water Uses</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2026-03-09","noUsgsAuthors":false,"plainLanguageSummary":"<p>This map shows the location of water permits and graphs of the reported amount of water used from those permits from rivers, streams, and wells as of July 2024, near Theodore Roosevelt National Park in North Dakota. Total water use in the map area &nbsp;more than doubled from 2020 to 2023. From 1980 through 2023, water from rivers and streams was used more than water from wells, but water use from wells began to increase starting in 2011. From 1980 through 2015, most water was used for irrigation, but after 2015, most water was used for industrial purposes.&nbsp;</p>","publicationDate":"2026-03-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Anderson, Todd M. 0000-0001-8971-9502","orcid":"https://orcid.org/0000-0001-8971-9502","contributorId":218978,"corporation":false,"usgs":true,"family":"Anderson","given":"Todd","email":"","middleInitial":"M.","affiliations":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":956899,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Medler, Colton J. 0000-0001-6119-5065","orcid":"https://orcid.org/0000-0001-6119-5065","contributorId":201463,"corporation":false,"usgs":true,"family":"Medler","given":"Colton","email":"","middleInitial":"J.","affiliations":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":956900,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70274135,"text":"70274135 - 2026 - Alternative future vegetation pathways reveal potential transformations of western US ecosystems","interactions":[],"lastModifiedDate":"2026-03-12T16:41:27.715088","indexId":"70274135","displayToPublicDate":"2026-03-09T11:34:07","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1837,"text":"Global Change Biology","active":true,"publicationSubtype":{"id":10}},"title":"Alternative future vegetation pathways reveal potential transformations of western US ecosystems","docAbstract":"<p><span>Managing ecosystems in an era of rapid change is inherently challenging not only because of uncertainty in future climate but also due to diverse responses of ecosystems to climate. Projections of ecological transformation alongside information about plausible vegetation trajectories can help land managers explore divergent scenarios and consider how modeled outcomes match their observations. Climate-analog impact models (AIMs) compare environmental information (e.g., vegetation types) between sets of climatically similar locations to infer change and can be used to identify multiple outcomes. We used AIMs to project changes in vegetation across the western United States under a mid-21st century climate scenario, characterize ecological transformation vulnerability based on projection divergence, and demonstrate how AIMs can inform decision-making. We projected high or very high vulnerability to ecological transformation across 29% of the western US, nearly 1 M km</span><sup>2</sup><span>. Vulnerability varied among vegetation groups; 75% of alpine vegetation had high or very high vulnerability vs. 6% of desert scrub. We estimate that 9% of the study area faces a high likelihood of transformation based on combined measures of vulnerability and projection agreement. Transformation at the vegetation type (</span><i>n</i><span> = 50) level is projected for 40% (1.4 M km</span><sup>2</sup><span>) of the study area, based on primary projections. As vegetation shifts towards types supported by a more arid climate, forested area is expected to contract by 9% and subalpine forests specifically by 54%. Elsewhere, vulnerability is low or trajectories are uncertain, implying opportunities for managers to intervene. Dry forests, for example, could be stabilized through vegetation management and intentional fire use. Our findings suggest likely ecological transformations with significant downstream consequences for ecosystem services and natural resources. They are best used within decision-making frameworks that draw on multiple lines of evidence including local expertise and complementary knowledge systems.</span></p>","language":"English","publisher":"Wiley","doi":"10.1111/gcb.70795","usgsCitation":"Hoecker, T.J., Davis, K.T., Littlefield, C.E., Chandler, J.C., Parks, S.A., Maguire, A., Kemp, K., Yegorova, S., and Dobrowski, S., 2026, Alternative future vegetation pathways reveal potential transformations of western US ecosystems: Global Change Biology, v. 32, no. 3, e70795, 15 p., https://doi.org/10.1111/gcb.70795.","productDescription":"e70795, 15 p.","ipdsId":"IP-182529","costCenters":[{"id":36940,"text":"National Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":501100,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/gcb.70795","text":"Publisher Index Page"},{"id":500990,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, California, Colorado, Idaho, Montana, Nevada, New Mexico, Oregon, Utah, Washington, Wyoming","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"MultiPolygon\",\"coordinates\":[[[[-104.053249,41.001406],[-102.124972,41.002338],[-102.051292,40.749591],[-102.04192,37.035083],[-102.979613,36.998549],[-103.002247,36.911587],[-103.064423,32.000518],[-106.565142,32.000736],[-106.577244,31.810406],[-106.750547,31.783706],[-108.208394,31.783599],[-108.208573,31.333395],[-111.000643,31.332177],[-114.813613,32.494277],[-114.722746,32.713071],[-117.118868,32.534706],[-117.50565,33.334063],[-118.088896,33.729817],[-118.428407,33.774715],[-118.519514,34.027509],[-119.159554,34.119653],[-119.616862,34.420995],[-120.441975,34.451512],[-120.608355,34.556656],[-120.644311,35.139616],[-120.873046,35.225688],[-120.884757,35.430196],[-121.851967,36.277831],[-121.932508,36.559935],[-121.788278,36.803994],[-121.880167,36.950151],[-122.140578,36.97495],[-122.419113,37.24147],[-122.511983,37.77113],[-122.425942,37.810979],[-122.168449,37.504143],[-122.144396,37.581866],[-122.385908,37.908136],[-122.301804,38.105142],[-122.484411,38.11496],[-122.492474,37.82484],[-122.972378,38.020247],[-123.103706,38.415541],[-123.725367,38.917438],[-123.851714,39.832041],[-124.373599,40.392923],[-124.063076,41.439579],[-124.536073,42.814175],[-124.150267,43.91085],[-123.962887,45.280218],[-123.996766,46.20399],[-123.548194,46.248245],[-124.029924,46.308312],[-124.06842,46.601397],[-123.97083,46.47537],[-123.84621,46.716795],[-124.022413,46.708973],[-124.108078,46.836388],[-123.86018,46.948556],[-124.138035,46.970959],[-124.425195,47.738434],[-124.672427,47.964414],[-124.727022,48.371101],[-123.981032,48.164761],[-122.748911,48.117026],[-122.637425,47.889945],[-123.15598,47.355745],[-122.527593,47.905882],[-122.578211,47.254804],[-122.725738,47.33047],[-122.691771,47.141958],[-122.796646,47.341654],[-122.863732,47.270221],[-122.67813,47.103866],[-122.364168,47.335953],[-122.429841,47.658919],[-122.230046,47.970917],[-122.425572,48.232887],[-122.358375,48.056133],[-122.512031,48.133931],[-122.424102,48.334346],[-122.689121,48.476849],[-122.425271,48.599522],[-122.796887,48.975026],[-104.048736,48.999877],[-104.053249,41.001406]]],[[[-119.789798,34.05726],[-119.5667,34.053452],[-119.795938,33.962929],[-119.916216,34.058351],[-119.789798,34.05726]]],[[[-118.524531,32.895488],[-118.573522,32.969183],[-118.369984,32.839273],[-118.524531,32.895488]]],[[[-118.500212,33.449592],[-118.32446,33.348782],[-118.593969,33.467198],[-118.500212,33.449592]]],[[[-122.519535,48.288314],[-122.66921,48.240614],[-122.400628,48.036563],[-122.419274,47.912125],[-122.744612,48.20965],[-122.664928,48.374823],[-122.519535,48.288314]]],[[[-122.800217,48.60169],[-122.883759,48.418793],[-123.173061,48.579086],[-122.949116,48.693398],[-122.743049,48.661991],[-122.800217,48.60169]]]]},\"properties\":{\"name\":\"Arizona\",\"nation\":\"USA  \"}}]}","volume":"32","issue":"3","noUsgsAuthors":false,"publicationDate":"2026-03-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Hoecker, Tyler J. 0000-0001-8680-8809","orcid":"https://orcid.org/0000-0001-8680-8809","contributorId":367051,"corporation":false,"usgs":false,"family":"Hoecker","given":"Tyler","middleInitial":"J.","affiliations":[{"id":84304,"text":"Vibrant Planet","active":true,"usgs":false}],"preferred":false,"id":956646,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Davis, Kimberley T. 0000-0001-9727-374X","orcid":"https://orcid.org/0000-0001-9727-374X","contributorId":355031,"corporation":false,"usgs":false,"family":"Davis","given":"Kimberley","middleInitial":"T.","affiliations":[{"id":84700,"text":"USDA - Rocky Mountain Research Station","active":true,"usgs":false}],"preferred":false,"id":956647,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Littlefield, Caitlin E. 0000-0003-3771-7956","orcid":"https://orcid.org/0000-0003-3771-7956","contributorId":220623,"corporation":false,"usgs":false,"family":"Littlefield","given":"Caitlin","email":"","middleInitial":"E.","affiliations":[{"id":36523,"text":"University of Montana","active":true,"usgs":false}],"preferred":false,"id":956648,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Chandler, Jeffrey C","contributorId":223870,"corporation":false,"usgs":false,"family":"Chandler","given":"Jeffrey","email":"","middleInitial":"C","affiliations":[{"id":40781,"text":"USDA/APHIS/WS, National Wildlife Research Center","active":true,"usgs":false}],"preferred":false,"id":956649,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Parks, Sean A. 0000-0002-2982-5255","orcid":"https://orcid.org/0000-0002-2982-5255","contributorId":225035,"corporation":false,"usgs":false,"family":"Parks","given":"Sean","email":"","middleInitial":"A.","affiliations":[{"id":41024,"text":"Aldo Leopold Wilderness Research Institute, Rocky Mountain Research Station","active":true,"usgs":false}],"preferred":false,"id":956650,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Maguire, Andy John 0000-0002-6334-0497","orcid":"https://orcid.org/0000-0002-6334-0497","contributorId":358945,"corporation":false,"usgs":true,"family":"Maguire","given":"Andy John","affiliations":[{"id":36940,"text":"National Climate Adaptation Science Center","active":true,"usgs":true}],"preferred":true,"id":956651,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kemp, Kerry","contributorId":367059,"corporation":false,"usgs":false,"family":"Kemp","given":"Kerry","affiliations":[{"id":36400,"text":"US Forest Service","active":true,"usgs":false}],"preferred":false,"id":956652,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Yegorova, Svetlana 0000-0003-3228-7379","orcid":"https://orcid.org/0000-0003-3228-7379","contributorId":367060,"corporation":false,"usgs":false,"family":"Yegorova","given":"Svetlana","affiliations":[{"id":34255,"text":"Wilfred Laurier University","active":true,"usgs":false}],"preferred":false,"id":956653,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Dobrowski, Solomon","contributorId":229621,"corporation":false,"usgs":false,"family":"Dobrowski","given":"Solomon","affiliations":[{"id":36523,"text":"University of Montana","active":true,"usgs":false}],"preferred":false,"id":956654,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70274636,"text":"70274636 - 2026 - Seasonal and hydrologic variation influences habitat and functional structure of stream fish assemblages","interactions":[],"lastModifiedDate":"2026-04-02T17:32:18.629216","indexId":"70274636","displayToPublicDate":"2026-03-08T10:25:49","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":16456,"text":"Frontiers in Enviornmental Science","active":true,"publicationSubtype":{"id":10}},"title":"Seasonal and hydrologic variation influences habitat and functional structure of stream fish assemblages","docAbstract":"<p class=\"TitleInline\"><strong>Introduction:<span>&nbsp;</span></strong></p><p>Hydrologic variability is a key driver of ecological structure in lotic systems, shaping habitat conditions, taxonomic diversity, and the functional traits that mediate species’ persistence and performance (e.g., reproductive success). While many studies examine taxonomic responses to variation in flows, few evaluate how spatiotemporal hydrologic variation influences the functional organization within stream fish communities.</p><p class=\"TitleInline\"><strong>Methods:<span>&nbsp;</span></strong></p><p>We quantified seasonal habitat structure and functional trait diversity of fish assemblages across six Ozark Plateau headwater streams representing two contrasting flow regimes: Groundwater Flashy and Runoff/Intermittent Flashy. Fish and habitat data were collected seasonally during a dry year (2002) and a wet year (2003). Functional space was constructed using PCoA of morphological, ecological, and life-history traits, and functional diversity was measured using community weighted means (CWMs), functional richness (FRic), functional evenness (FEve), and functional divergence (FDiv).</p><p class=\"TitleInline\"><strong>Results:<span>&nbsp;</span></strong></p><p>We found that habitat structure differed strongly by flow regime and season, with Runoff/Intermittent streams exhibiting pronounced reductions in depth, area, and velocity, while groundwater streams remained structurally stable. Functional identity of assemblages was similar across flow regimes, dominated by benthic, hydrodynamic taxa with opportunistic and periodic life-history strategies. However, functional structure differed significantly: FEve and FDiv were consistently lower in Runoff/Intermittent Flashy streams in both years, indicating assemblage dominance of species with similar trait combinations and reduced trait partitioning under variable flow. FRic and taxonomic richness remained stable across seasons and flow regimes, suggesting high functional redundancy despite species turnover.</p><p class=\"TitleInline\"><strong>Discussion:<span>&nbsp;</span></strong></p><p>Together, results show that flow regime mediates both habitat structural stability and functional organization. As climatic warming and extreme drought increase hydrologic instability in headwaters, functional trait approaches provide a sensitive tool for detecting losses of functional roles that may not be evident by using taxonomic metrics alone.</p><p><br data-mce-bogus=\"1\"></p>","language":"English","publisher":"Frontiers Media","doi":"10.3389/fenvs.2026.1764275","usgsCitation":"Tevin, J.D., and Magoulick, D.D., 2026, Seasonal and hydrologic variation influences habitat and functional structure of stream fish assemblages: Frontiers in Enviornmental Science, v. 14, 1764275, 12 p., https://doi.org/10.3389/fenvs.2026.1764275.","productDescription":"1764275, 12 p.","ipdsId":"IP-183893","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":502093,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fenvs.2026.1764275","text":"Publisher Index Page"},{"id":502018,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arkansas, Kansas, Missouri, Oklahoma","otherGeospatial":"Ozark Plateau","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -93.87853545078246,\n              38.81177292452688\n            ],\n            [\n              -94.85631736224987,\n              37.49831555285621\n            ],\n            [\n              -95.0816237179703,\n              36.012743986836\n            ],\n            [\n              -96.47425582357388,\n              35.473500987699396\n            ],\n            [\n              -96.8316306490365,\n              34.53761869055651\n            ],\n            [\n              -94.38173262709171,\n              34.13947518555052\n            ],\n            [\n              -91.82173207075576,\n              34.51573263843926\n            ],\n            [\n              -90.24360144566828,\n              37.41865191298166\n            ],\n            [\n              -90.67449039663896,\n              38.57755110007105\n            ],\n            [\n              -93.87853545078246,\n              38.81177292452688\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"14","noUsgsAuthors":false,"publicationDate":"2026-03-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Tevin, Joshua D.","contributorId":369130,"corporation":false,"usgs":false,"family":"Tevin","given":"Joshua","middleInitial":"D.","affiliations":[{"id":6623,"text":"University of Arkansas","active":true,"usgs":false}],"preferred":false,"id":958505,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Magoulick, Daniel D. 0000-0001-9665-5957 danmag@usgs.gov","orcid":"https://orcid.org/0000-0001-9665-5957","contributorId":2513,"corporation":false,"usgs":true,"family":"Magoulick","given":"Daniel","email":"danmag@usgs.gov","middleInitial":"D.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":958506,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70274560,"text":"70274560 - 2026 - Estimating discharge from undular hydraulic jumps: Feasibility assessment based on flume experiments","interactions":[],"lastModifiedDate":"2026-03-30T15:40:22.34149","indexId":"70274560","displayToPublicDate":"2026-03-07T10:28:17","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Estimating discharge from undular hydraulic jumps: Feasibility assessment based on flume experiments","docAbstract":"<p><span>Rapids are common in steep rivers, often forming where flow transitions from supercritical (Froude number,&nbsp;</span><i>Fr</i><span>&nbsp;&gt;&nbsp;1) to subcritical (</span><i>Fr</i><span>&nbsp;&lt;&nbsp;1) through a hydraulic jump. When upstream&nbsp;</span><i>Fr</i><span>&nbsp;is supercritical but close to 1, this transition may occur as an undular hydraulic jump, exhibiting a train of stationary waves downstream of the jump toe. Previous studies proposed a method to estimate discharge using only UHJ wave spacing and channel width combined with a wave dispersion equation for large water depths relative to the UHJ wavelength. This method is based on the hypotheses that, by their presence, UHJs indicate near-critical flow conditions (</span><i>Fr</i><span> ≈</span><span>&nbsp;1) and that wave celerity&nbsp;</span><i>c</i><span>&nbsp;is equal to and opposite the cross-sectionally averaged flow velocity&nbsp;</span><i>U</i><span>. However, these hypotheses have not been thoroughly tested. We used data from published UHJ flume experiments to test the hypotheses that&nbsp;</span><i>Fr</i><span> ≈</span><span>&nbsp;1 and&nbsp;</span><i>c</i><span>&nbsp;=&nbsp;</span><i>U</i><span>, compare the deep-water and general wave dispersion equations, and evaluate the accuracy of discharge estimates. In these experiments, the stationary waves exhibited shallow depths relative to wavelength and flow was subcritical (</span><i>Fr</i><span>&nbsp;&lt;&nbsp;1) when averaged across multiple wavelengths. Additionally, wave celerity more closely approximated the surface flow velocity than&nbsp;</span><i>U</i><span>. By using a&nbsp;</span><i>Fr</i><span>&nbsp;representative of actual conditions and applying a coefficient to correct for <i>c</i> ≠ <i>U</i> </span><span>, the accuracy of the discharge estimates improved. This finding suggests that the critical flow-based method is robust and can produce reliable streamflow estimates if the remotely observed wave trains are correctly interpreted as UHJs, without requiring in situ measurements.</span></p>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2025WR040997","usgsCitation":"White, D., Yager, E., Legleiter, C.J., Grant, G., Hempel, L.A., Leonard, C.M., Adler, K., Harlan, M.E., and Fasth, B., 2026, Estimating discharge from undular hydraulic jumps: Feasibility assessment based on flume experiments: Water Resources Research, v. 62, no. 3, e2025WR040997, 19 p., https://doi.org/10.1029/2025WR040997.","productDescription":"e2025WR040997, 19 p.","ipdsId":"IP-172038","costCenters":[{"id":501,"text":"Office of Science Quality and Integrity","active":true,"usgs":true},{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true}],"links":[{"id":502062,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2025wr040997","text":"Publisher Index Page"},{"id":501815,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"62","issue":"3","noUsgsAuthors":false,"publicationDate":"2026-03-07","publicationStatus":"PW","contributors":{"authors":[{"text":"White, Daniel  C. 0000-0001-8376-8469","orcid":"https://orcid.org/0000-0001-8376-8469","contributorId":347543,"corporation":false,"usgs":false,"family":"White","given":"Daniel  C.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":958310,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yager, Elowyn 0000-0002-3382-2356","orcid":"https://orcid.org/0000-0002-3382-2356","contributorId":347542,"corporation":false,"usgs":false,"family":"Yager","given":"Elowyn","affiliations":[{"id":36394,"text":"University of Idaho","active":true,"usgs":false}],"preferred":false,"id":958311,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Legleiter, Carl J. 0000-0003-0940-8013 cjl@usgs.gov","orcid":"https://orcid.org/0000-0003-0940-8013","contributorId":169002,"corporation":false,"usgs":true,"family":"Legleiter","given":"Carl","email":"cjl@usgs.gov","middleInitial":"J.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":958312,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Grant, Gordon","contributorId":349384,"corporation":false,"usgs":false,"family":"Grant","given":"Gordon","affiliations":[{"id":83479,"text":"US Forest Service, Oregon State University","active":true,"usgs":false}],"preferred":false,"id":958313,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hempel, Laura A. 0000-0001-5020-6056","orcid":"https://orcid.org/0000-0001-5020-6056","contributorId":224286,"corporation":false,"usgs":true,"family":"Hempel","given":"Laura","email":"","middleInitial":"A.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":958314,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Leonard, Christina M. 0000-0002-5096-8103","orcid":"https://orcid.org/0000-0002-5096-8103","contributorId":360578,"corporation":false,"usgs":false,"family":"Leonard","given":"Christina","middleInitial":"M.","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":958315,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Adler, Katherine","contributorId":369026,"corporation":false,"usgs":false,"family":"Adler","given":"Katherine","affiliations":[],"preferred":false,"id":958316,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Harlan, Merritt Elizabeth 0000-0002-4019-4888","orcid":"https://orcid.org/0000-0002-4019-4888","contributorId":302672,"corporation":false,"usgs":true,"family":"Harlan","given":"Merritt","email":"","middleInitial":"Elizabeth","affiliations":[{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true}],"preferred":true,"id":958317,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Fasth, Becky","contributorId":349390,"corporation":false,"usgs":false,"family":"Fasth","given":"Becky","affiliations":[{"id":6604,"text":"University of Oregon","active":true,"usgs":false}],"preferred":false,"id":958318,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70274666,"text":"70274666 - 2026 - Development and assessment of fluorescent-dyed, preserved invasive grass carp (Ctenopharyngodon idella) eggs as surrogates for live eggs in transport and dispersal control experiments","interactions":[],"lastModifiedDate":"2026-04-03T15:31:04.627511","indexId":"70274666","displayToPublicDate":"2026-03-07T10:24:19","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3301,"text":"River Research and Applications","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Development and assessment of fluorescent-dyed, preserved invasive grass carp (<i>Ctenopharyngodon idella</i>) eggs as surrogates for live eggs in transport and dispersal control experiments","title":"Development and assessment of fluorescent-dyed, preserved invasive grass carp (Ctenopharyngodon idella) eggs as surrogates for live eggs in transport and dispersal control experiments","docAbstract":"<p><span>Invasive species such as grass carp (</span><i>Ctenopharyngodon idella</i><span>) pose substantial ecological threats to North American freshwater ecosystems. Understanding their early life stage behavior is critical for management efforts. From spawning to hatching, invasive carp eggs must remain suspended in the water column while drifting downstream for the best chance of survival. This highly vulnerable life stage is a potential target for population control to reduce recruitment. However, studying egg transport and potential dispersal control techniques is challenging, because the availability of live eggs and time period for experimentation are extremely limited. Additionally, accurately replicating the physical characteristics and transport mechanisms of fish eggs using surrogates in laboratory and field studies is not trivial. This study presents a novel method to create fluorescein-dyed, preserved grass carp eggs as surrogates for live eggs in transport and dispersal control experiments. This technique enables year-round studies of grass carp egg transport, offering managers a reliable tool for developing and testing dispersal control and passive sampling methods for invasive carp eggs. In this study, we rehydrate and dye preserved grass carp eggs in varying concentrations of aqueous fluorescein for a range of rehydration times, evaluate dye retention and egg visibility under ultraviolet light (UV-A), and measure diameters and settling velocities for comparison with live eggs. Eggs rehydrated in 0.100 g per liter fluorescein for 30 min maintain adequate brightness for up to 40 min in mixed conditions and exhibit mean settling velocities and densities similar to live eggs, making them ideal for laboratory experiments using quantitative imaging techniques.</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/rra.70124","usgsCitation":"Doyle, H.F., Stahlschmidt, B.H., Herndon, A.M., Prasad, V., George, A.E., Fischer, J.R., Jackson, P.R., Cory D. Suski, and Tinoco, R.O., 2026, Development and assessment of fluorescent-dyed, preserved invasive grass carp (Ctenopharyngodon idella) eggs as surrogates for live eggs in transport and dispersal control experiments: River Research and Applications, https://doi.org/10.1002/rra.70124.","ipdsId":"IP-172670","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":502461,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/rra.70124","text":"Publisher Index Page"},{"id":502166,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"edition":"Online First","noUsgsAuthors":false,"publicationDate":"2026-03-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Doyle, Henry F. 0000-0001-9942-8602","orcid":"https://orcid.org/0000-0001-9942-8602","contributorId":369222,"corporation":false,"usgs":false,"family":"Doyle","given":"Henry","middleInitial":"F.","affiliations":[{"id":16984,"text":"University of Illinois at Urbana-Champaign","active":true,"usgs":false}],"preferred":false,"id":958621,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stahlschmidt, Benjamin H. 0000-0001-6197-662X","orcid":"https://orcid.org/0000-0001-6197-662X","contributorId":211250,"corporation":false,"usgs":true,"family":"Stahlschmidt","given":"Benjamin","email":"","middleInitial":"H.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":958622,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Herndon, Anne Marie 0000-0002-7057-0303","orcid":"https://orcid.org/0000-0002-7057-0303","contributorId":332776,"corporation":false,"usgs":true,"family":"Herndon","given":"Anne","email":"","middleInitial":"Marie","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":958623,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Prasad, Vindhyawasini 0000-0003-0585-7217","orcid":"https://orcid.org/0000-0003-0585-7217","contributorId":296287,"corporation":false,"usgs":false,"family":"Prasad","given":"Vindhyawasini","email":"","affiliations":[{"id":16984,"text":"University of Illinois at Urbana-Champaign","active":true,"usgs":false}],"preferred":false,"id":958624,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"George, Amy E. 0000-0003-1150-8646 ageorge@usgs.gov","orcid":"https://orcid.org/0000-0003-1150-8646","contributorId":3950,"corporation":false,"usgs":true,"family":"George","given":"Amy","email":"ageorge@usgs.gov","middleInitial":"E.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":958625,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Fischer, Jesse Robert 0000-0002-9071-7931","orcid":"https://orcid.org/0000-0002-9071-7931","contributorId":329677,"corporation":false,"usgs":true,"family":"Fischer","given":"Jesse","email":"","middleInitial":"Robert","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":958626,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Jackson, P. Ryan 0000-0002-3154-6108 pjackson@usgs.gov","orcid":"https://orcid.org/0000-0002-3154-6108","contributorId":194529,"corporation":false,"usgs":true,"family":"Jackson","given":"P.","email":"pjackson@usgs.gov","middleInitial":"Ryan","affiliations":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true},{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":958627,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Cory D. Suski","contributorId":369224,"corporation":false,"usgs":false,"family":"Cory D. Suski","affiliations":[{"id":16984,"text":"University of Illinois at Urbana-Champaign","active":true,"usgs":false}],"preferred":false,"id":958628,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Tinoco, Rafael O.","contributorId":211779,"corporation":false,"usgs":false,"family":"Tinoco","given":"Rafael","email":"","middleInitial":"O.","affiliations":[{"id":38317,"text":"Department of Civil and Environmental Engineering, University of Illinois at Urbana-Champaign, Urbana, IL","active":true,"usgs":false}],"preferred":false,"id":958629,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70274277,"text":"70274277 - 2026 - Satellite time series analysis to quantify changing climax ciénegas using a state and transition model approach","interactions":[],"lastModifiedDate":"2026-03-24T17:12:07.583859","indexId":"70274277","displayToPublicDate":"2026-03-07T10:02:44","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1456,"text":"Ecological Indicators","active":true,"publicationSubtype":{"id":10}},"title":"Satellite time series analysis to quantify changing climax ciénegas using a state and transition model approach","docAbstract":"<p><span id=\"_mce_caret\" data-mce-bogus=\"1\" data-mce-type=\"format-caret\"><span>Ciénegas are rare wetlands in arid landscapes of the North American Southwest, historically providing critical ecological and hydrological functions but increasingly threatened by changing climate and land use pressures. This study quantifies changes in ciénega condition and floodplain dynamics using a state-and-transition model (STM) informed by expert knowledge and remote sensing. Key factors include woody plant encroachment, water availability, and soil aggradation. We mapped 31 ciénegas with high-resolution imagery and analyzed Landsat data (1985–2023) to assess vegetation health and moisture using the Normalized Difference Vegetation Index (NDVI) and Normalized Difference Infrared Index (NDII). Results show substantial interannual variability in phenology, water stress, and soil moisture, with regional drying and elevation strongly influencing ciénega resilience. We classified ciénegas into three functional states—healthy, desiccated, and dormant—and mapped their 2023 condition. Trend analyses indicate most ciénegas exhibit greening despite drought, though localized variability underscores the need for site-specific management. None are in a stable climax (reference) state; rather, they transition among states in response to external drivers. Increasing woody plant cover and surface drying, likely linked to declining regional water tables, favor deep-rooted species over wetland grasses—a pattern mirrored in adjacent control plots. Spatially explicit analysis revealed intra-ciénega variability often masked by aggregated data, highlighting the importance of high-resolution monitoring. Seasonal and long-term trends provide context for understanding ciénega dynamics, including degradation and restoration pathways. This study emphasizes the importance of groundwater conservation and demonstrates how remote sensing supports long-term monitoring. The STM framework offers a practical tool for adaptive management to sustain freshwater resources in arid environments.</span></span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolind.2026.114741","usgsCitation":"Norman, L., Petrakis, R.E., Wilson, N.R., Middleton, B.R., Villarreal, M.L., Pollock, M., Minckley, T.A., and Hendrickson, D., 2026, Satellite time series analysis to quantify changing climax ciénegas using a state and transition model approach: Ecological Indicators, v. 184, 114741, 16 p., https://doi.org/10.1016/j.ecolind.2026.114741.","productDescription":"114741, 16 p.","ipdsId":"IP-179305","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":501684,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecolind.2026.114741","text":"Publisher Index Page"},{"id":501477,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Mexico, United States","state":"Arizona, New Mexico","otherGeospatial":"Sonora","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -112.05152972005978,\n              33.0768867725987\n            ],\n            [\n              -112.05152972005978,\n              29.88732922369421\n            ],\n            [\n              -108.36301240182003,\n              29.88732922369421\n            ],\n            [\n              -108.36301240182003,\n              33.0768867725987\n            ],\n            [\n              -112.05152972005978,\n              33.0768867725987\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"184","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Norman, Laura M. 0000-0002-3696-8406","orcid":"https://orcid.org/0000-0002-3696-8406","contributorId":203300,"corporation":false,"usgs":true,"family":"Norman","given":"Laura M.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":957547,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Petrakis, Roy E. 0000-0001-8932-077X rpetrakis@usgs.gov","orcid":"https://orcid.org/0000-0001-8932-077X","contributorId":174623,"corporation":false,"usgs":true,"family":"Petrakis","given":"Roy","email":"rpetrakis@usgs.gov","middleInitial":"E.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":957548,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wilson, Natalie R. 0000-0001-5145-1221 nrwilson@usgs.gov","orcid":"https://orcid.org/0000-0001-5145-1221","contributorId":214982,"corporation":false,"usgs":true,"family":"Wilson","given":"Natalie","email":"nrwilson@usgs.gov","middleInitial":"R.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":957549,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Middleton, Barry R.","contributorId":367728,"corporation":false,"usgs":false,"family":"Middleton","given":"Barry","middleInitial":"R.","affiliations":[{"id":36921,"text":"Ret. USGS","active":true,"usgs":false}],"preferred":false,"id":957550,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Villarreal, Miguel L. 0000-0003-0720-1422 mvillarreal@usgs.gov","orcid":"https://orcid.org/0000-0003-0720-1422","contributorId":214980,"corporation":false,"usgs":true,"family":"Villarreal","given":"Miguel","email":"mvillarreal@usgs.gov","middleInitial":"L.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":957551,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Pollock, Michael","contributorId":367729,"corporation":false,"usgs":false,"family":"Pollock","given":"Michael","affiliations":[{"id":38436,"text":"National Oceanic and Atmospheric Administration","active":true,"usgs":false}],"preferred":false,"id":957552,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Minckley, Thomas A.","contributorId":367730,"corporation":false,"usgs":false,"family":"Minckley","given":"Thomas","middleInitial":"A.","affiliations":[{"id":87617,"text":"University of Wyoming, Department of Geology and Geophysics, Laramie, WY 82071-2000","active":true,"usgs":false}],"preferred":false,"id":957553,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hendrickson, Dean","contributorId":367731,"corporation":false,"usgs":false,"family":"Hendrickson","given":"Dean","affiliations":[{"id":87618,"text":"University of Texas at Austin, College of Natural Sciences, Austin, TX 78712","active":true,"usgs":false}],"preferred":false,"id":957554,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70274196,"text":"ofr20261063 - 2026 - Evaluation of turbidity corrections for EXO fluorescent dissolved organic matter (fDOM) sensors","interactions":[],"lastModifiedDate":"2026-03-06T21:45:10.353284","indexId":"ofr20261063","displayToPublicDate":"2026-03-06T11:20:00","publicationYear":"2026","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2026-1063","displayTitle":"Evaluation of Turbidity Corrections for EXO Fluorescent Dissolved Organic Matter (fDOM) Sensors","title":"Evaluation of turbidity corrections for EXO fluorescent dissolved organic matter (fDOM) sensors","docAbstract":"<h1>Executive Summary&nbsp;</h1><p>The use of field-deployable fluorescence sensors to better understand dissolved organic matter concentrations and composition has grown immensely in recent years. Applications of these sensors to critical monitoring efforts have also grown, encompassing post-fire monitoring, wastewater tracking, and use as a proxy for various contaminants. Despite the growth, it is well known that these sensors require corrections for temperature (Watras and others, 2011) and are subject to many light-field interferences caused by both scattering and absorbance due to dissolved and particulate substances (Downing and others, 2012; Lee and others, 2015; Booth and others, 2023). The most common fluorescence sensors used by the U.S. Geological Survey (USGS) include those targeting fluorescent dissolved organic matter (fDOM) and chlorophylls. Because fDOM sensors primarily measure fluorescence in the dissolved to colloidal phases, corrections to the interferences caused by particulates can be made relatively easily. By the end of 2024, the USGS had 69 fDOM sensors deployed within official water quality monitoring networks included on the USGS National Water Dashboard (<a data-mce-href=\"https://dashboard.waterdata.usgs.gov/app/nwd/en/\" href=\"https://dashboard.waterdata.usgs.gov/app/nwd/en/\" target=\"_blank\" rel=\"noopener\">https://dashboard.waterdata.usgs.gov/app/nwd/en/</a>) and numerous others used in surveys and research applications across the Nation.</p><p>Although temperature corrections are widely applicable across sensor models, interference corrections can be model specific due to differences in design specifications across manufacturers and models (Booth and others, 2023). The corrections are also potentially subject to changes in manufacturing within a specific sensor model. Recently, USGS staff obtained information regarding possible changes in the manufacturing of its most widely-used fDOM sensor model, raising concerns about data consistency and quality in the USGS fDOM sensor networks.</p><p>Furthermore, changes in turbidity sensors since the corrections guidance was performed may also affect the performance of the corrections. The turbidity sensor used in the original experiments (Downing and others, 2012) was determined to have a signal output approximately 1.3 times higher than the output of the turbidity sensor currently used in an extensive field comparison study (Messner and others, 2023). With these changes, it is imperative that the corrections be reevaluated to maintain data consistency and continuity across the USGS.</p><p>In this study, we evaluated turbidity corrections for fDOM sensors over a range of serial numbers covering manufacturing dates 2015 through 2022 and turbidity serial numbers covering the range 2013 through 2022. The goal was to determine whether reported changes in the manufacturing process of the fDOM and turbidity sensors affected the correction approach developed by Downing and others (2012) such that additional guidance would be required to address this manufacturing change. To evaluate, we repeated a laboratory-based test similar to that performed by Downing and others (2012) in which a series of tank experiments with multiple sensors were deployed in a suspension of Elliot Silt Loam (ESL). High turbidities of the ESL suspension were maintained throughout the tank by turbulent recirculation using submersible pumps. Particulates were removed using a recirculated line equipped with a capsule filter (0.45 micron). Measurements were collected throughout the filtration until turbidities reached approximately 5 formazin nephelometric units (FNU; data available in Baxter and others, 2023). Each experimental run included a mixture of unique sensor combinations to account for variability imposed by the turbidity and temperature sensors. The fDOM correction factor was calculated for each combination of fDOM and turbidity sensors included in the test.</p><p>We observed no systematic change in fDOM correction coefficients across serial numbers representing manufacturing years 2015 through 2022. However, the results highlighted questions raised about the corrections for high-turbidity samples, as noted in USGS Techniques and Methods (Booth and others, 2023). Applying the inverse of the commonly-used fDOM ratio with a quadratic fit performed better than the exponential fits when correcting fDOM data for turbidity in the ESL laboratory filtration test and generated a simple scale factor correction equation. This approach also served as a better indicator of data quality than the exponential fit approach. Similar to fDOM, more rigorous quality assurance measures may be necessary to evaluate turbidity sensor calibrations and performance. Sensors exceeding a certain age may need to be replaced despite passing quality assurance checks during calibration. Further testing of the turbidity corrections for different sediment and water types is warranted to better understand the variations in the fits and correctable ranges of turbidity in different systems.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20261063","programNote":"Water Resources Mission Area","usgsCitation":"Fleck, J.A., Baxter, T.J., and Hansen, A.M., 2026, Evaluation of turbidity corrections for fluorescent dissolved organic matter (fDOM) sensors: U.S. Geological Survey Open-File Report 2026–1063, 30 p., https://doi.org/10.3133/ofr20261063.","productDescription":"Report: vi, 30 p.; Data Release","numberOfPages":"30","onlineOnly":"Y","ipdsId":"IP-171907","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":500842,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2026/1063/coverthb.jpg"},{"id":500843,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2026/1063/ofr20261063.pdf","text":"Report","size":"2.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2026-1063 PDF"},{"id":500844,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20261063/full","linkFileType":{"id":5,"text":"html"},"description":"OFR 2026-1063 HTML"},{"id":500845,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2026/1063/ofr20261063.XML","linkFileType":{"id":8,"text":"xml"},"description":"OFR 2026-1063 XML"},{"id":500846,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2026/1063/images"},{"id":500847,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9OB430E","text":"USGS data release","linkHelpText":"Fluorescence sensor measurements in sediment suspensions to evaluate turbidity corrections"}],"contact":"<p><a href=\"mailto:dc_ca@usgs.gov\" data-mce-href=\"mailto:dc_ca@usgs.gov\">Director</a>,&nbsp;<a href=\"https://ca.water.usgs.gov/\" data-mce-href=\"https://ca.water.usgs.gov/\">California Water Science Center</a><br><a href=\"https://www.usgs.gov/\" data-mce-href=\"https://www.usgs.gov/\">U.S. Geological Survey</a><br>6000 J Street, Placer Hall<br>Sacramento, California 95819</p>","tableOfContents":"<ul><li>Executive Summary</li><li>Introduction</li><li>Background</li><li>Description of Technology, Sensor, or Method</li><li>Results of Laboratory Testing</li><li>Summary and Conclusions</li><li>Acknowledgements</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"publishedDate":"2026-03-06","noUsgsAuthors":false,"publicationDate":"2026-03-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Fleck, Jacob 0000-0002-3217-3972 jafleck@usgs.gov","orcid":"https://orcid.org/0000-0002-3217-3972","contributorId":168694,"corporation":false,"usgs":true,"family":"Fleck","given":"Jacob","email":"jafleck@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":956901,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Baxter, Tim James 0009-0005-6781-6455","orcid":"https://orcid.org/0009-0005-6781-6455","contributorId":331639,"corporation":false,"usgs":true,"family":"Baxter","given":"Tim James","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":956902,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hansen, Angela 0000-0003-0938-7611 anhansen@usgs.gov","orcid":"https://orcid.org/0000-0003-0938-7611","contributorId":171551,"corporation":false,"usgs":true,"family":"Hansen","given":"Angela","email":"anhansen@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":956903,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70275023,"text":"70275023 - 2026 - Evaluating alternative methods for modeling trap efficiencies of out-migrating juvenile salmonids","interactions":[],"lastModifiedDate":"2026-04-13T15:16:23.481012","indexId":"70275023","displayToPublicDate":"2026-03-06T10:12:56","publicationYear":"2026","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":"Evaluating alternative methods for modeling trap efficiencies of out-migrating juvenile salmonids","docAbstract":"<div class=\" sec\"><div class=\"title\">Objective</div><p class=\"chapter-para\">We aimed to compare two machine learning approaches—boosted beta regression (BBR) and beta mixed model forest (BMF)—to a Bayesian mixed-effects beta regression (BME) for the prediction of rotary screw trap (RST) efficiency for out-migrating juvenile salmonids from environmental covariates.</p></div><div class=\" sec\"><div class=\"title\">Methods</div><p class=\"chapter-para\">We identified two machine learning approaches that shared the ability to model overdispersed probabilities. We compared the BBR and BMF machine learning models to a BME model to evaluate precision in detection probability prediction and model performance on bias in parameter estimation. We tested our three candidate models using a simulation study to understand the specific advantages and disadvantages of each when the data set was increasingly sparse and the capture probabilities were realistically small. We then applied the models to a case study of RST data from the Klamath River in California, United States.</p></div><div class=\" sec\"><div class=\"title\">Results</div><p class=\"chapter-para\">The BME and BMF outperformed BBR in all simulated scenarios, although the BMF displayed poor explanatory power. In the case study, the BME and BMF identified environmental covariates that predicted RST efficiency.</p></div><div class=\" sec\"><div class=\"title\">Conclusions</div><p class=\"chapter-para\">Using the BME as a benchmark for comparing machine learning approaches to trap efficiency modeling, our simulations and case study demonstrated that the BMF performed well and is a viable modeling approach with strong predictive power. The BME model would be the preferred modeling approach when its strong explanatory power is desired.</p></div>","language":"English","publisher":"Oxford Academic","doi":"10.1093/najfmt/vqag005","usgsCitation":"Walden, M.A., and Som, N., 2026, Evaluating alternative methods for modeling trap efficiencies of out-migrating juvenile salmonids: North American Journal of Fisheries Management, v. 46, no. 2, p. 478-494, https://doi.org/10.1093/najfmt/vqag005.","productDescription":"17 p.","startPage":"478","endPage":"494","ipdsId":"IP-172641","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":503001,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/najfmt/vqag005","text":"Publisher Index Page"},{"id":502748,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"46","issue":"2","noUsgsAuthors":false,"publicationDate":"2026-03-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Walden, M. A.","contributorId":369812,"corporation":false,"usgs":false,"family":"Walden","given":"M.","middleInitial":"A.","affiliations":[{"id":37071,"text":"California State Polytechnic University","active":true,"usgs":false}],"preferred":false,"id":959224,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Som, Nicholas A 0009-0006-9722-6330","orcid":"https://orcid.org/0009-0006-9722-6330","contributorId":356271,"corporation":false,"usgs":true,"family":"Som","given":"Nicholas A","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":959225,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70274683,"text":"70274683 - 2026 - Assessing environmental drivers of denitrification in restored riverine floodplains","interactions":[],"lastModifiedDate":"2026-04-06T15:03:50.286337","indexId":"70274683","displayToPublicDate":"2026-03-06T09:52:23","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":23785,"text":"Journal of Ecological Engineering Design","active":true,"publicationSubtype":{"id":10}},"title":"Assessing environmental drivers of denitrification in restored riverine floodplains","docAbstract":"<p><span>Restoration of impaired floodplains is an increasingly prevalent strategy for alleviating water quality concerns and reducing downstream flooding at watershed scales. Floodplains temporarily store water and slow flow velocity to promote sedimentation during overbank flooding and remove inorganic nitrogen from floodwater and groundwater via denitrification. Evaluating the impacts of different restoration strategies on denitrification can inform more strategic investments into floodplain modifications that improve water quality outcomes. Our research investigates how denitrification rates in floodplains respond to environmental factors that are actionable from an engineering perspective through design and water resources management. We seasonally measured soil denitrification enzyme activity and various environmental characteristics in 4 floodplains with different restoration design and management approaches at the confluence of the Wabash and Tippecanoe Rivers in Indiana, United States. Our results showed that denitrification rates in an agricultural floodplain were significantly lower than in restored floodplains with native vegetation. Certain soil conditions characteristic of floodplain wetlands were associated with higher denitrification, particularly elevated total nitrogen, moisture, silt, and organic matter contents. Vegetation species composition was correlated with denitrification rates. This link may reflect the direct effects of vegetation on soil conditions, such as supplying labile organic carbon, or indirect effects, such as vegetation acting as an indicator of hydrologic regime and land use. Denitrification seasonally varied, peaking in winter when nitrate supply from rivers draining agricultural watersheds in the region is also high. Substrate limitation of soil denitrification enzyme activity was most significant during the summer when overbank flooding, which replenishes soil nitrogen stocks, rarely occurs. Our findings indicate that denitrification capacity will likely be maximized in riverine floodplains that are restored as wetlands with diverse native vegetation and enhanced hydrologic connectivity. Such restoration activities promote higher denitrification rates via elevated moisture, fine sediment deposition, and soil organic matter.</span></p>","language":"English","publisher":"University of Vermont Press","doi":"10.70793/jeed.13","usgsCitation":"Lay, D.W., McMillan, S.W., Hosen, J.D., Dey, S., and Noe, G.E., 2026, Assessing environmental drivers of denitrification in restored riverine floodplains: Journal of Ecological Engineering Design, v. 4, no. 1, 17 p., https://doi.org/10.70793/jeed.13.","productDescription":"17 p.","ipdsId":"IP-179949","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":502474,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.70793/jeed.13","text":"Publisher Index Page"},{"id":502206,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Tippecanoe River, Wabash River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -86.73421342718163,\n              40.54578001376902\n            ],\n            [\n              -86.77854172394578,\n              40.56893409536539\n            ],\n            [\n              -86.85226822336595,\n              40.486689152088985\n            ],\n            [\n              -86.83272067583472,\n              40.46994703338217\n            ],\n            [\n              -86.73421342718163,\n              40.54578001376902\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"4","issue":"1","noUsgsAuthors":false,"publicationDate":"2026-03-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Lay, Danielle Winter","contributorId":369252,"corporation":false,"usgs":false,"family":"Lay","given":"Danielle","middleInitial":"Winter","affiliations":[{"id":13186,"text":"Purdue University","active":true,"usgs":false}],"preferred":false,"id":958691,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McMillan, Sara W.","contributorId":369253,"corporation":false,"usgs":false,"family":"McMillan","given":"Sara","middleInitial":"W.","affiliations":[{"id":6911,"text":"Iowa State University","active":true,"usgs":false}],"preferred":false,"id":958692,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hosen, Jacob D.","contributorId":369254,"corporation":false,"usgs":false,"family":"Hosen","given":"Jacob","middleInitial":"D.","affiliations":[{"id":13186,"text":"Purdue University","active":true,"usgs":false}],"preferred":false,"id":958693,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dey, Sayan","contributorId":369255,"corporation":false,"usgs":false,"family":"Dey","given":"Sayan","affiliations":[{"id":30787,"text":"Saint Louis University","active":true,"usgs":false}],"preferred":false,"id":958694,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Noe, Gregory E. 0000-0002-6661-2646 gnoe@usgs.gov","orcid":"https://orcid.org/0000-0002-6661-2646","contributorId":139100,"corporation":false,"usgs":true,"family":"Noe","given":"Gregory","email":"gnoe@usgs.gov","middleInitial":"E.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true}],"preferred":true,"id":958695,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70275205,"text":"70275205 - 2026 - Stream macroinvertebrate responses vary with region, land use and management practice type","interactions":[],"lastModifiedDate":"2026-04-22T14:34:11.340833","indexId":"70275205","displayToPublicDate":"2026-03-06T09:21:44","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2258,"text":"Journal of Environmental Management","active":true,"publicationSubtype":{"id":10}},"title":"Stream macroinvertebrate responses vary with region, land use and management practice type","docAbstract":"<p><span>Intensive land use alters hydrology and water quality, threatening freshwater benthic macroinvertebrates. Over 200,000 management practices (MPs) have been implemented across the Chesapeake Bay watershed since the 1980s, yet biological responses remain inconsistent. We synthesized 29 studies from 4 physiographic provinces covering 8&nbsp;MP categories and evaluated macroinvertebrate responses along MP gradients using structural (richness), functional (biomass), tolerance, and biotic metrics. We hypothesized that MPs enhancing habitat complexity or restoring flow regimes would benefit taxa sensitive to sediment, hydrologic instability and organic pollution, with outcomes shaped by regional context, land use, and chosen metrics. Four themes emerged. (i) Agricultural Riparian Forest Buffers (RFBs) consistently improved sensitive metrics related to abundance, biomass and richness. (ii) Urban streams with Stream Habitat Improvement and Management (SHIM) showed improved richness and diversity, but biomass and tolerance metrics declined or remained neutral, indicating unresolved hydrologic and pollutant stress. (iii) Structural and functional responses diverged: effect sizes for total and feeding-group biomasses (functional metrics) were negative, whereas genus-level Ephemeroptera-Plecoptera-Trichoptera (EPT) richness (structural metric) was positive, indicating that structural shifts may not track underlying production changes. (iv) Physiographic comparisons showed counterintuitive patterns, as RFBs improved EPT richness in Piedmont streams but had negative effects in the Coastal Plain. Evaluating MP effectiveness requires distinguishing a no-MP pathway (stressors → instream conditions → assemblages → responses) from an MP-mediated pathway (practice regime → modified stressors → instream conditions → assemblages → responses), underscoring the need for region-specific, multi-metric monitoring and improved understanding of MP density thresholds and recovery lags.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jenvman.2026.129172","collaboration":"Virginia Tech, USGS","usgsCitation":"Sabat-Bonilla, S.A., Belvin, A.C., Noe, G.E., Maloney, K.O., Frimpong, E.A., Angermeier, P., and Entrekin. Sally E., 2026, Stream macroinvertebrate responses vary with region, land use and management practice type: Journal of Environmental Management, v. 403, 129172, 14 p., https://doi.org/10.1016/j.jenvman.2026.129172.","productDescription":"129172, 14 p.","ipdsId":"IP-181470","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":503441,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jenvman.2026.129172","text":"Publisher Index Page"},{"id":503299,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"eastern contiguous United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -101.0436249,\n              29.3328733\n            ],\n            [\n              -99.6425005,\n              27.5074215\n            ],\n            [\n              -98.8640981,\n              26.211199\n            ],\n            [\n              -97.3591867,\n              25.8848423\n            ],\n            [\n              -96.9440387,\n              27.8291374\n            ],\n            [\n              -93.6747485,\n              29.4233134\n            ],\n            [\n              -89.2638014,\n              28.9703115\n            ],\n            [\n              -85.7350438,\n              29.5136731\n            ],\n            [\n              -84.0744519,\n              29.6490614\n            ],\n            [\n              -81.7392446,\n              25.0885121\n            ],\n            [\n              -80.1824398,\n              24.9003778\n            ],\n            [\n              -79.8191853,\n              26.5366431\n            ],\n            [\n              -81.1684162,\n              31.3037444\n            ],\n            [\n              -75.0968772,\n              35.2926383\n            ],\n            [\n              -75.4082382,\n              37.5061126\n            ],\n            [\n              -73.2287114,\n              40.0542222\n            ],\n            [\n              -71.9832675,\n              41.0008498\n            ],\n            [\n              -69.3885927,\n              41.5856895\n            ],\n            [\n              -70.0632082,\n              42.2421607\n            ],\n            [\n              -72.450309,\n              41.1573197\n            ],\n            [\n              -73.5400724,\n              41.1963789\n            ],\n            [\n              -73.6438594,\n              43.1574323\n            ],\n            [\n              -77.6396585,\n              43.1574323\n            ],\n            [\n              -81.7911381,\n              41.2744275\n            ],\n            [\n              -86.3577657,\n              34.4838855\n            ],\n            [\n              -88.5372925,\n              37.5884002\n            ],\n            [\n              -92.5849851,\n              34.5266496\n            ],\n            [\n              -97.9300151,\n              34.6121119\n            ],\n            [\n              -98.8122046,\n              31.4809337\n            ],\n            [\n              -101.0436249,\n              29.3328733\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"403","noUsgsAuthors":false,"publicationDate":"2026-03-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Sabat-Bonilla, Sergio A.","contributorId":370289,"corporation":false,"usgs":false,"family":"Sabat-Bonilla","given":"Sergio","middleInitial":"A.","affiliations":[{"id":25550,"text":"Virginia Polytechnic Institute and State University","active":true,"usgs":false}],"preferred":false,"id":960116,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Belvin, Abigail C.","contributorId":370290,"corporation":false,"usgs":false,"family":"Belvin","given":"Abigail","middleInitial":"C.","affiliations":[{"id":25550,"text":"Virginia Polytechnic Institute and State University","active":true,"usgs":false}],"preferred":false,"id":960117,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Noe, Gregory E. 0000-0002-6661-2646 gnoe@usgs.gov","orcid":"https://orcid.org/0000-0002-6661-2646","contributorId":139100,"corporation":false,"usgs":true,"family":"Noe","given":"Gregory","email":"gnoe@usgs.gov","middleInitial":"E.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":960118,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Maloney, Kelly O. 0000-0003-2304-0745 kmaloney@usgs.gov","orcid":"https://orcid.org/0000-0003-2304-0745","contributorId":4636,"corporation":false,"usgs":true,"family":"Maloney","given":"Kelly","email":"kmaloney@usgs.gov","middleInitial":"O.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":960119,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Frimpong, Emmanuel A.","contributorId":370293,"corporation":false,"usgs":false,"family":"Frimpong","given":"Emmanuel","middleInitial":"A.","affiliations":[{"id":25550,"text":"Virginia Polytechnic Institute and State University","active":true,"usgs":false}],"preferred":false,"id":960120,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Angermeier, Paul L. 0000-0003-2864-170X","orcid":"https://orcid.org/0000-0003-2864-170X","contributorId":204519,"corporation":false,"usgs":true,"family":"Angermeier","given":"Paul L.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":960121,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Entrekin. Sally E.","contributorId":370299,"corporation":false,"usgs":false,"family":"Entrekin. Sally E.","affiliations":[{"id":25550,"text":"Virginia Polytechnic Institute and State University","active":true,"usgs":false}],"preferred":false,"id":960122,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70274543,"text":"70274543 - 2026 - Working group on American Eel (WGAMEEL; outputs from 2024 meeting)","interactions":[],"lastModifiedDate":"2026-03-31T14:32:51.150531","indexId":"70274543","displayToPublicDate":"2026-03-06T08:54:37","publicationYear":"2026","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":3,"text":"Organization Series"},"seriesTitle":{"id":23776,"text":"ICES Scientific Reports","active":true,"publicationSubtype":{"id":3}},"title":"Working group on American Eel (WGAMEEL; outputs from 2024 meeting)","docAbstract":"<p dir=\"ltr\">The Working Group on American Eel (WGAMEEL) met virtually three times in 2022-2024 to address the five Terms of Reference (ToRs) of its three-year term. The first two ToRs tasked WGAMEEL with listing and evaluating data on American eel landings, abundance indices, and spatial and habitat data and also to describe assessment methods used in Canada and the US. Canada-wide American eel trajectory was estimated using 12 fishery-independent datasets. Generally, longer datasets had more negative trends than shorter ones. Limiting data to the post-2000 years produced fewer negative trends that did not differ from zero, suggesting the observed declines occurred pre-2000. Spatial modelling for American eel requires knowledge and mapping that covers the breadth of habitat types occupied by the species, including freshwater, estuarine, and marine environments. In recent years there has been an expansion of online databases with data from the aquatic environment, particularly in freshwater, with estuarine and marine data less consistently documented. This report broadly compiles abiotic data series of relevance to American eel. A larger challenge for spatial modelling will be acquiring enough high quality, georeferenced biological data sets with suitable observations to assess occurrence, abundance, and trends over time in a spatial framework.</p><p dir=\"ltr\">The third ToR considered Indigenous Knowledge Systems for American eel. A survey reaching First Nations representatives from four Canadian provinces confirmed the cultural importance of eels in Indigenous communities, and that Indigenous knowledge possessed by the participant groups are place-based and contextual, especially regarding threats impacting eels.</p><p dir=\"ltr\">The final two ToRs focused on identifying stock assessment modelling approaches applicable to American and European eel, and assessing whether any of these approaches might be appropriate for American eel management moving forward. WGAMEEL evaluated the various approaches for assessing American eel or providing management advice. Two approaches that could be completed in the next few years because of their minimal data needs are index-based methods and catch-only method. A suite of approaches considered by WGAMEEL that would take more time and data were spatial or habitat models, management strategy evaluation, and spawner-per-recruit (SPR) models potentially paired with meta-population models.</p>","language":"English","publisher":"International Council for the Exploration of the Sea","doi":"10.17895/ices.pub.31538731","usgsCitation":"April, J., Anstead, K., Brodeur, P., Cairns, D., Castonguay, M., Cieri, M., Jessop, B., D'Astous, A., Denny, S., Dumont, J., Eyler, S., Koops, M.A., Lee, L., Landry-Massicote, L., Maxwell, R., Pratt, T., Reid, S.M., Roloson, S., Schlueter, S.L., Snyder, S., and Young, J.A., 2026, Working group on American Eel (WGAMEEL; outputs from 2024 meeting): ICES Scientific Reports, v. 8, no. 15, 68 p., https://doi.org/10.17895/ices.pub.31538731.","productDescription":"68 p.","ipdsId":"IP-174599","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":501856,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","issue":"15","noUsgsAuthors":false,"publicationDate":"2026-03-06","publicationStatus":"PW","contributors":{"editors":[{"text":"Anstead, Kristen A.","contributorId":329847,"corporation":false,"usgs":false,"family":"Anstead","given":"Kristen","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":958372,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Pratt, Thomas","contributorId":347389,"corporation":false,"usgs":false,"family":"Pratt","given":"Thomas","affiliations":[{"id":13677,"text":"Fisheries and Oceans Canada","active":true,"usgs":false}],"preferred":false,"id":958373,"contributorType":{"id":2,"text":"Editors"},"rank":2}],"authors":[{"text":"April, Julien","contributorId":369015,"corporation":false,"usgs":false,"family":"April","given":"Julien","affiliations":[{"id":87698,"text":"Ministère de l'Environnement, de la Lutte contre les changements climatiques, de la Faune et des Parcs","active":true,"usgs":false}],"preferred":false,"id":958374,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Anstead, Kristen A.","contributorId":348307,"corporation":false,"usgs":false,"family":"Anstead","given":"Kristen A.","affiliations":[{"id":83332,"text":"Atlantic States Marine Fisheries Commission","active":true,"usgs":false}],"preferred":false,"id":958375,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brodeur, Philippe","contributorId":369056,"corporation":false,"usgs":false,"family":"Brodeur","given":"Philippe","affiliations":[],"preferred":false,"id":958376,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cairns, David K.","contributorId":292427,"corporation":false,"usgs":false,"family":"Cairns","given":"David K.","affiliations":[{"id":13677,"text":"Fisheries and Oceans Canada","active":true,"usgs":false}],"preferred":false,"id":958214,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Castonguay, Martin","contributorId":292432,"corporation":false,"usgs":false,"family":"Castonguay","given":"Martin","email":"","affiliations":[{"id":13677,"text":"Fisheries and Oceans Canada","active":true,"usgs":false}],"preferred":false,"id":958377,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cieri, Matthew","contributorId":369058,"corporation":false,"usgs":false,"family":"Cieri","given":"Matthew","affiliations":[],"preferred":false,"id":958378,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Jessop, Brian","contributorId":369057,"corporation":false,"usgs":false,"family":"Jessop","given":"Brian","affiliations":[],"preferred":false,"id":958379,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"D'Astous, Amelie","contributorId":369059,"corporation":false,"usgs":false,"family":"D'Astous","given":"Amelie","affiliations":[],"preferred":false,"id":958380,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Denny, Shelly","contributorId":369060,"corporation":false,"usgs":false,"family":"Denny","given":"Shelly","affiliations":[],"preferred":false,"id":958381,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Dumont, Jean-Francois","contributorId":369061,"corporation":false,"usgs":false,"family":"Dumont","given":"Jean-Francois","affiliations":[],"preferred":false,"id":958382,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Eyler, Sheila","contributorId":189779,"corporation":false,"usgs":false,"family":"Eyler","given":"Sheila","affiliations":[],"preferred":false,"id":958383,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Koops, Marten A.","contributorId":16715,"corporation":false,"usgs":false,"family":"Koops","given":"Marten","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":958384,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Lee, Laura","contributorId":369062,"corporation":false,"usgs":false,"family":"Lee","given":"Laura","affiliations":[],"preferred":false,"id":958385,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Landry-Massicote, Louis","contributorId":369063,"corporation":false,"usgs":false,"family":"Landry-Massicote","given":"Louis","affiliations":[],"preferred":false,"id":958386,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Maxwell, 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Scott","contributorId":368986,"corporation":false,"usgs":false,"family":"Roloson","given":"Scott","affiliations":[{"id":87695,"text":"Canadian Department of Fisheries and Oceans.","active":true,"usgs":false}],"preferred":false,"id":958213,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Schlueter, Scott L.","contributorId":197961,"corporation":false,"usgs":false,"family":"Schlueter","given":"Scott","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":958390,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Snyder, Shawn","contributorId":302899,"corporation":false,"usgs":false,"family":"Snyder","given":"Shawn","affiliations":[{"id":7063,"text":"University of Maine","active":true,"usgs":false}],"preferred":false,"id":958391,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Young, John A. 0000-0002-4500-3673","orcid":"https://orcid.org/0000-0002-4500-3673","contributorId":360717,"corporation":false,"usgs":true,"family":"Young","given":"John","middleInitial":"A.","affiliations":[{"id":85817,"text":"EESC (retired)","active":true,"usgs":false}],"preferred":true,"id":958212,"contributorType":{"id":1,"text":"Authors"},"rank":21}]}}
,{"id":70275040,"text":"70275040 - 2026 - Top-down targeted network analysis of critical mineral commodities applied to international geochemistry database","interactions":[],"lastModifiedDate":"2026-04-13T15:14:22.960342","indexId":"70275040","displayToPublicDate":"2026-03-06T08:09:39","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2302,"text":"Journal of Geochemical Exploration","active":true,"publicationSubtype":{"id":10}},"title":"Top-down targeted network analysis of critical mineral commodities applied to international geochemistry database","docAbstract":"<p><span id=\"_mce_caret\" data-mce-bogus=\"1\" data-mce-type=\"format-caret\"><span>The global demand for critical mineral commodities is rapidly increasing, making domestic production an important factor in supporting the economy and national security. Large scale, publicly available geochemical databases allow for the application of data informatics methods to interrogate critical mineral commodities data for correlations in deposit formation and distribution, particularly for identifying enrichment of multiple critical mineral commodities at the same deposit. In this study, we applied network analysis to the Critical Minerals Mapping Initiative (CMMI) ore geochemistry (Critical Minerals in Ores, CMiO) database to identify the high concentration (defined as 10× bulk crustal abundance) co-occurrence of different critical mineral commodities across a mineral system hierarchy from deposit environments to individual deposits. Identifying patterns or unique outliers in enrichment in network communities will allow for the location of secondary critical mineral commodity resources from under-utilized deposits. We find trends in the enrichment of critical mineral commodities in network-communities between the elements praseodymium (Pr), neodymium (Nd), terbium (Tb), and dysprosium (Dy) across multiple CMiO database deposit environments and groups down to specific deposit types and sites. A separate trend in network community deposition is observed as well between iridium (Ir) and platinum (Pt) in deposit environments, groups, types, and sites. Network analysis focused on critical minerals in magmatic-hydrothermal deposits identified multiple deposit sites from different deposit types within the CMiO database with concentrations of Dy, Nd, Tb, Pr, Ir, and Pt that are at least ten times greater than the crustal average. This approach can be applied to any target element(s) or deposit(s) of interest, allowing broad investigation of co-enriched critical mineral commodities.</span></span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.gexplo.2026.108032","usgsCitation":"Moore, E.K., Rosera, J.M., and Lederer, G.W., 2026, Top-down targeted network analysis of critical mineral commodities applied to international geochemistry database: Journal of Geochemical Exploration, v. 285, 108032, 14 p., https://doi.org/10.1016/j.gexplo.2026.108032.","productDescription":"108032, 14 p.","ipdsId":"IP-180176","costCenters":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":503000,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.gexplo.2026.108032","text":"Publisher Index Page"},{"id":502747,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"285","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Moore, Elisha Kelly 0000-0002-9750-7769","orcid":"https://orcid.org/0000-0002-9750-7769","contributorId":334043,"corporation":false,"usgs":true,"family":"Moore","given":"Elisha","email":"","middleInitial":"Kelly","affiliations":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"preferred":true,"id":959287,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rosera, Joshua Mark 0000-0003-3807-5000","orcid":"https://orcid.org/0000-0003-3807-5000","contributorId":270284,"corporation":false,"usgs":true,"family":"Rosera","given":"Joshua","email":"","middleInitial":"Mark","affiliations":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"preferred":true,"id":959288,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lederer, Graham W. 0000-0002-9505-9923","orcid":"https://orcid.org/0000-0002-9505-9923","contributorId":202407,"corporation":false,"usgs":true,"family":"Lederer","given":"Graham","email":"","middleInitial":"W.","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":true,"id":959289,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70274250,"text":"70274250 - 2026 - A framework for integrating spatiotemporal deep learning methods with landsat for annual land cover and impervious surface mapping","interactions":[],"lastModifiedDate":"2026-03-19T19:31:01.642826","indexId":"70274250","displayToPublicDate":"2026-03-05T14:20:03","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3254,"text":"Remote Sensing of Environment","printIssn":"0034-4257","active":true,"publicationSubtype":{"id":10}},"title":"A framework for integrating spatiotemporal deep learning methods with landsat for annual land cover and impervious surface mapping","docAbstract":"<div id=\"sp0075\" class=\"u-margin-s-bottom\">Land cover information is essential for understanding Earth’s surface dynamics and how vegetation, water, soil, climate, and terrain interact. The National Land Cover Database (NLCD) has been the authoritative source for consistent U.S. land cover mapping. To extend NLCD’s temporal resolution and reduce production latency, we developed the Land Cover Artificial Mapping System (LCAMS)—a prototype spatiotemporal deep learning framework piloted as the foundation for the new Annual NLCD.</div><div class=\"u-margin-s-bottom\"><br data-mce-bogus=\"1\"></div><div id=\"sp0080\" class=\"u-margin-s-bottom\">LCAMS builds on concepts from legacy NLCD and the U.S. Geological Survey Land Change Monitoring, Assessment, and Projection (LCMAP) initiatives. It employs a loosely coupled two-stage architecture consisting of independent but functionally interdependent spatial and temporal models. Spatial models extract per-year information from Landsat data, while the temporal models refine the spatial outputs to enforce inter-annual consistency—critical for reliable land change monitoring. LCAMS produces annual 30 m resolution land cover and impervious surface outputs, with region-specific fine-tuning to generalize across diverse landscapes and temporal dynamics.</div><div class=\"u-margin-s-bottom\"><br data-mce-bogus=\"1\"></div><div id=\"sp0085\" class=\"u-margin-s-bottom\">Validation was conducted using an independent dataset of 1925 randomly sampled plots from five U.S. Landsat Analysis Ready Data (ARD) tiles spanning 1985-2021, selected for spatial and temporal variability. This dataset was used consistently to evaluate LCAMS, Legacy NLCD, and LCMAP. Using the NLCD legend, LCAMS achieved<span> 72.1 ± 1.60%</span><span class=\"math\"><span id=\"MathJax-Element-1-Frame\" class=\"MathJax_SVG\" data-mathml=\"&lt;math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;&gt;&lt;mn is=&quot;true&quot;&gt;72.1&lt;/mn&gt;&lt;mo linebreak=&quot;goodbreak&quot; is=&quot;true&quot;&gt;&amp;#xB1;&lt;/mo&gt;&lt;mn is=&quot;true&quot;&gt;1.60&lt;/mn&gt;&lt;mi mathvariant=&quot;normal&quot; is=&quot;true&quot;&gt;%&lt;/mi&gt;&lt;/math&gt;\"></span></span><span>&nbsp;</span>overall agreement, compared to<span> 71.1 ± 1.7%</span><span class=\"math\"><span id=\"MathJax-Element-2-Frame\" class=\"MathJax_SVG\" data-mathml=\"&lt;math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;&gt;&lt;mn is=&quot;true&quot;&gt;71.1&lt;/mn&gt;&lt;mo linebreak=&quot;goodbreak&quot; is=&quot;true&quot;&gt;&amp;#xB1;&lt;/mo&gt;&lt;mn is=&quot;true&quot;&gt;1.7&lt;/mn&gt;&lt;mi mathvariant=&quot;normal&quot; is=&quot;true&quot;&gt;%&lt;/mi&gt;&lt;/math&gt;\"></span></span><span>&nbsp;</span>agreement for Legacy NLCD. Using the LCMAP legend, LCAMS achieved<span> 83.4 ±</span><span class=\"math\"><span id=\"MathJax-Element-3-Frame\" class=\"MathJax_SVG\" data-mathml=\"&lt;math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;&gt;&lt;mn is=&quot;true&quot;&gt;83.4&lt;/mn&gt;&lt;mo linebreak=&quot;goodbreak&quot; is=&quot;true&quot;&gt;&amp;#xB1;&lt;/mo&gt;&lt;mn is=&quot;true&quot;&gt;1.22&lt;/mn&gt;&lt;mi mathvariant=&quot;normal&quot; is=&quot;true&quot;&gt;%&lt;/mi&gt;&lt;/math&gt;\"></span></span><span> 1.22% </span>agreement, compared to 84.6<span> ±</span><span class=\"math\"><span id=\"MathJax-Element-4-Frame\" class=\"MathJax_SVG\" data-mathml=\"&lt;math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;&gt;&lt;mn is=&quot;true&quot;&gt;84.6&lt;/mn&gt;&lt;mo linebreak=&quot;goodbreak&quot; is=&quot;true&quot;&gt;&amp;#xB1;&lt;/mo&gt;&lt;mn is=&quot;true&quot;&gt;1.11&lt;/mn&gt;&lt;mi mathvariant=&quot;normal&quot; is=&quot;true&quot;&gt;%&lt;/mi&gt;&lt;/math&gt;\"></span></span><span> 1.11% </span>agreement for LCMAP. Overall, LCAMS delivers comparable accuracy while offering higher thematic resolution, longer temporal coverage, and automated production of annual 30 m CONUS land cover.</div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.rse.2026.115347","usgsCitation":"Fleckenstein, R., Wellington, D.F., Jin, S., Tollerud, H.J., Brown, J.F., Dewitz, J., Pastick, N.J., Barber, C.P., O'Brien, A., and Spanier, M., 2026, A framework for integrating spatiotemporal deep learning methods with landsat for annual land cover and impervious surface mapping: Remote Sensing of Environment, v. 338, 115347, 24 p., https://doi.org/10.1016/j.rse.2026.115347.","productDescription":"115347, 24 p.","ipdsId":"IP-178890","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":501373,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.rse.2026.115347","text":"Publisher Index Page"},{"id":501334,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"338","noUsgsAuthors":false,"publicationDate":"2026-03-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Fleckenstein, Rylie 0009-0000-1278-869X","orcid":"https://orcid.org/0009-0000-1278-869X","contributorId":351830,"corporation":false,"usgs":false,"family":"Fleckenstein","given":"Rylie","affiliations":[{"id":68993,"text":"KBR Inc., Contractor to the USGS","active":true,"usgs":false}],"preferred":false,"id":957169,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wellington, Danika Fay 0000-0002-2130-0075","orcid":"https://orcid.org/0000-0002-2130-0075","contributorId":225199,"corporation":false,"usgs":true,"family":"Wellington","given":"Danika","email":"","middleInitial":"Fay","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":957170,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jin, Suming 0000-0001-9919-8077 sjin@usgs.gov","orcid":"https://orcid.org/0000-0001-9919-8077","contributorId":4397,"corporation":false,"usgs":true,"family":"Jin","given":"Suming","email":"sjin@usgs.gov","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":957171,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Tollerud, Heather J. 0000-0001-9507-4456","orcid":"https://orcid.org/0000-0001-9507-4456","contributorId":210820,"corporation":false,"usgs":true,"family":"Tollerud","given":"Heather","email":"","middleInitial":"J.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":957172,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Brown, Jesslyn F. 0000-0002-9976-1998 jfbrown@usgs.gov","orcid":"https://orcid.org/0000-0002-9976-1998","contributorId":176609,"corporation":false,"usgs":true,"family":"Brown","given":"Jesslyn","email":"jfbrown@usgs.gov","middleInitial":"F.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":957173,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dewitz, Jon 0000-0002-0458-212X","orcid":"https://orcid.org/0000-0002-0458-212X","contributorId":222454,"corporation":false,"usgs":true,"family":"Dewitz","given":"Jon","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":957174,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Pastick, Neal J. 0000-0002-8169-3018 njpastick@usgs.gov","orcid":"https://orcid.org/0000-0002-8169-3018","contributorId":4785,"corporation":false,"usgs":true,"family":"Pastick","given":"Neal","email":"njpastick@usgs.gov","middleInitial":"J.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":957175,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Barber, Christopher P. 0000-0003-0570-1140","orcid":"https://orcid.org/0000-0003-0570-1140","contributorId":223102,"corporation":false,"usgs":true,"family":"Barber","given":"Christopher","middleInitial":"P.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":957176,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"O'Brien, Austin","contributorId":367239,"corporation":false,"usgs":false,"family":"O'Brien","given":"Austin","affiliations":[],"preferred":false,"id":957177,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Spanier, Mark","contributorId":367240,"corporation":false,"usgs":false,"family":"Spanier","given":"Mark","affiliations":[],"preferred":false,"id":957178,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70274178,"text":"fs20263001 - 2026 - Landsat 8–9 geometric and radiometric calibration and characterization","interactions":[],"lastModifiedDate":"2026-03-06T14:39:50.839838","indexId":"fs20263001","displayToPublicDate":"2026-03-05T13:46:40","publicationYear":"2026","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2026-3001","displayTitle":"Landsat 8–9 Geometric and Radiometric Calibration and Characterization","title":"Landsat 8–9 geometric and radiometric calibration and characterization","docAbstract":"<p>The U.S. Geological Survey Earth Resources Observation and Science Cal/Val (Calibration and Validation) Center of Excellence is a global leader in improving the accuracy, precision, and quality of remote-sensing data. Calibration is the process of quantitatively defining a system’s response to known and controlled signal inputs. Validation is the process of assessing, by independent means, the quality of the calibrated data products derived from system outputs.&nbsp;</p><p>The Landsat Cal/Val team, comanaged by the Earth Resources Observation and Science Cal/Val Center of Excellence and the National Aeronautics and Space Administration Landsat Science Project, continually monitors the geometric and radiometric performance of active Landsat missions and makes calibration adjustments, as needed, to maintain data quality at the highest level, ensuring its reliability for scientific research. Landsat data quality is often referred to as the “gold standard” and gives other civil and commercial satellite programs a trusted reference point for measuring their own data quality.&nbsp;</p><p>The Landsat program started more than 50 years ago. Since then, Landsat missions have gone through multiple technological advances, which, together with improved calibration and validation techniques, have led to higher data quality over time. The Cal/Val team also maintains consistency in data calibration across the multiple generations of sensors, which is vital to many scientists for time-series analysis.&nbsp;</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20263001","usgsCitation":"Anderson, C., Choate, M.J., Micijevic, E., and Shaw, J.L., 2026, Landsat 8–9 geometric and radiometric calibration and characterization: U.S. Geological Survey Fact Sheet 2026–3001, 4 p., https://doi.org/10.3133/fs20263001.","productDescription":"4 p.","numberOfPages":"4","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-177245","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":500745,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/fs20263001/full"},{"id":500741,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2026/3001/coverthb.jpg"},{"id":500742,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2026/3001/fs20263001.pdf","text":"Report","size":"8.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2026-3001"},{"id":500743,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/fs/2026/3001/fs20263001.XML"},{"id":500744,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/fs/2026/3001/images/"}],"contact":"<p class=\"ColophonPara\" style=\"mso-layout-grid-align: none; text-autospace: none;\" data-mce-style=\"mso-layout-grid-align: none; text-autospace: none;\"><span style=\"mso-bidi-font-size: 12.0pt; line-height: 200%;\" data-mce-style=\"mso-bidi-font-size: 12.0pt; line-height: 200%;\"><a data-mce-href=\"mailto:eccoe@usgs.gov\" href=\"mailto:eccoe@usgs.gov\">Project team</a>, <a data-mce-href=\"https://www.usgs.gov/calval\" href=\"https://www.usgs.gov/calval\">Earth Resources Observation and Science (EROS) Cal/Val Center of Excellence (ECCOE)</a><br>U.S. Geological Survey<br></span><span style=\"mso-bidi-font-size: 12.0pt; line-height: 200%;\" data-mce-style=\"mso-bidi-font-size: 12.0pt; line-height: 200%;\">47914 252nd Street<br></span><span style=\"mso-bidi-font-size: 12.0pt; line-height: 200%;\" data-mce-style=\"mso-bidi-font-size: 12.0pt; line-height: 200%;\">Sioux Falls, SD 57198</span></p>","tableOfContents":"<ul><li>Overview of Landsat 8–9 Sensors</li><li>Geometric and Radiometric Characterization and Calibration</li><li>Landsat 8–9 Data Correction</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2026-03-05","noUsgsAuthors":false,"publicationDate":"2026-03-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Anderson, Cody 0000-0001-5612-1889 chanderson@usgs.gov","orcid":"https://orcid.org/0000-0001-5612-1889","contributorId":195521,"corporation":false,"usgs":true,"family":"Anderson","given":"Cody","email":"chanderson@usgs.gov","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":956785,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Choate, Michael J. 0000-0002-8101-4994","orcid":"https://orcid.org/0000-0002-8101-4994","contributorId":268248,"corporation":false,"usgs":true,"family":"Choate","given":"Michael J.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":956786,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Micijevic, Esad 0000-0002-3828-9239 emicijevic@usgs.gov","orcid":"https://orcid.org/0000-0002-3828-9239","contributorId":3075,"corporation":false,"usgs":true,"family":"Micijevic","given":"Esad","email":"emicijevic@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":956787,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shaw, Jerad L. 0000-0002-8319-2778","orcid":"https://orcid.org/0000-0002-8319-2778","contributorId":270396,"corporation":false,"usgs":false,"family":"Shaw","given":"Jerad L.","affiliations":[{"id":40546,"text":"KBR, Contractor to the USGS Earth Resources Observation and Science (EROS) Center","active":true,"usgs":false}],"preferred":false,"id":956788,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70274172,"text":"ofr20261064 - 2026 - Monitoring nesting waterbirds for the South Bay Salt Pond Restoration Project—2024 breeding season","interactions":[],"lastModifiedDate":"2026-03-06T14:46:41.679118","indexId":"ofr20261064","displayToPublicDate":"2026-03-05T11:04:56","publicationYear":"2026","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2026-1064","displayTitle":"Monitoring Nesting Waterbirds for the South Bay Salt Pond Restoration Project—2024 Breeding Season","title":"Monitoring nesting waterbirds for the South Bay Salt Pond Restoration Project—2024 breeding season","docAbstract":"<p>The San Francisco Bay supports thousands of breeding waterbirds annually and hosts large populations of American avocets (<i>Recurvirostra americana</i>), black-necked stilts (<i>Himantopus mexicanus</i>), and Forster’s terns (<i>Sterna forsteri</i>). These three species have relied largely on former commercial salt ponds in south San Francisco Bay, which provide wetland foraging habitat and island nesting habitat. The South Bay Salt Pond Restoration Project is in the process of restoring as much as 15,100 acres of these former salt ponds to tidal marsh and tidal mudflats. Although this restoration is expected to have numerous benefits, including providing habitat for tidal wetland-dependent species, improving water quality, buffering against storm surge, and protecting inland areas from sea level rise, the reduction in former salt-pond habitat and nesting islands may negatively affect breeding waterbirds. To address the reduction in former salt-pond habitat available to waterbirds, the South Bay Salt Pond Restoration Project will maintain some pond habitat for wildlife and provide enhancements such as the construction of new islands for nesting. The South Bay Salt Pond Restoration Project follows an adaptive management plan in which waterbird response to the changing landscape is monitored over time to ensure that existing breeding waterbird populations are maintained.</p><p>In this report, we provide results of waterbird nest monitoring in south San Francisco Bay during the 2024 breeding season and present these results in the context of annual nest monitoring in south San Francisco Bay since 2005. Overall, Forster’s tern nest abundance in 2024 (1,808 nests) was the highest recorded between 2005 and 2024, and it maintained the high abundance first observed in 2022 (1,727 nests), which reversed the historically low abundance observed during 2015–17. In contrast, nest abundance remained at or near 20-year lows for American avocets (222 nests) and black-necked stilts (126 nests) in 2024, but both species had small increases in their nesting population sizes compared to 2022. In 2024, there were only 3 Forster’s tern, 5 American avocet, and 3 black-necked stilt major colony nesting sites, which is down from the annual averages of 6.6, 12.4, and 6.6 observed during 2005–09. Nest success (73 percent for American avocets, 54 percent for black-necked stilt, and 64 percent for Forster’s terns) increased compared to 2022 (30 percent for American avocets, 29 percent for black-necked stilt, and 53 percent for Forster’s terns) and during 2005–10 (37 percent for American avocets, 24 percent for black-necked stilt, and 61 percent for Forster’s terns). Nest success in 2024 was above (American avocets and black-necked stilts) or slightly below (Forster’s terns) baseline values established for the South Bay Salt Pond Restoration Project. Average egg-hatching success was lower for American avocets (86 percent) and Forster’s terns (86 percent) and similar for black-necked stilts (96 percent) than the values observed during 2005–10. Average clutch sizes for American avocets (3.87 eggs), black-necked stilts (3.88 eggs), and Forster’s terns (2.73 eggs) were greater than what was observed in 2022 and during 2005–10. Average nest-initiation dates in 2024 were substantially earlier among all three species (April 19 for American avocets, April 25 for black-necked stilts, and May 12 for Forster’s terns) than in 2022 (May 4 for American avocets, May 13 for black-necked stilts, and May 20 for Forster’s terns) and during 2005–10 (May 15 for American avocets, May 3 for black-necked stilts, and May 30 for Forster’s terns). Finally, the enhanced managed ponds with newly constructed islands (Ponds A16 and SF2) supported 52 percent of American avocet nests, 47 percent of black-necked stilt nests, and 94 percent of all the Forster’s tern nests recorded in south San Francisco Bay in 2024.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20261064","collaboration":"Prepared in cooperation with the California State Coastal Conservancy, California Wildlife Foundation, California Department of Fish and Wildlife, U.S. Fish and Wildlife Service, and South Bay Salt Pond Restoration Project","programNote":"Ecosystems Mission Area—Land Management Research Program and Species Management Research Program","usgsCitation":"Ackerman, J.T., Hartman, C.A., and Herzog, M., 2026, Monitoring nesting waterbirds for the South Bay Salt Pond Restoration Project—2024 breeding season: U.S. Geological Survey Open-File Report 2026–1064, 27 p., https://doi.org/10.3133/ofr20261064.","productDescription":"Report: vi, 27 p.; Data Release","numberOfPages":"27","onlineOnly":"Y","ipdsId":"IP-177737","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":500738,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P13VVTPR","text":"USGS data release","linkHelpText":"Waterbird nest abundance in south San Francisco Bay"},{"id":500737,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2026/1064/images"},{"id":500736,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2026/1064/ofr20261064.XML","linkFileType":{"id":8,"text":"xml"},"description":"OFR 2026-1064 XML"},{"id":500733,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2026/1064/coverthb.jpg"},{"id":500734,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2026/1064/ofr20261064.pdf","text":"Report","size":"4.15 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2026-1064 PDF"},{"id":500735,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20261064/full","linkFileType":{"id":5,"text":"html"},"description":"OFR 2026-1064 HTML"}],"country":"United States","state":"California","otherGeospatial":"south San Francisco Bay","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -122.25,\n              37.667\n            ],\n            [\n              -122.25,\n              37.4167\n            ],\n            [\n              -121.9,\n              37.4167\n            ],\n            [\n              -121.9,\n              37.667\n            ],\n            [\n              -122.25,\n              37.667\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","contact":"<p><a href=\"https://www.usgs.gov/centers/werc\" data-mce-href=\"https://www.usgs.gov/centers/werc\">Western Ecological Research Center</a><br><a href=\"https://www.usgs.gov/\" data-mce-href=\"https://www.usgs.gov/\">U.S. Geological Survey</a><br>3020 State University Drive East<br>Sacramento, California 95819</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Methods</li><li>Results and Discussion</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"publishedDate":"2026-03-05","noUsgsAuthors":false,"publicationDate":"2026-03-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Ackerman, Joshua T. 0000-0002-3074-8322","orcid":"https://orcid.org/0000-0002-3074-8322","contributorId":202848,"corporation":false,"usgs":true,"family":"Ackerman","given":"Joshua","middleInitial":"T.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":956775,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hartman, C. Alex 0000-0002-7222-1633 chartman@usgs.gov","orcid":"https://orcid.org/0000-0002-7222-1633","contributorId":131157,"corporation":false,"usgs":true,"family":"Hartman","given":"C.","email":"chartman@usgs.gov","middleInitial":"Alex","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":956783,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Herzog, Mark P. 0000-0002-5203-2835 mherzog@usgs.gov","orcid":"https://orcid.org/0000-0002-5203-2835","contributorId":131158,"corporation":false,"usgs":true,"family":"Herzog","given":"Mark","email":"mherzog@usgs.gov","middleInitial":"P.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":956784,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70274192,"text":"ofr20261066 - 2026 - Floods of June 2024 in northwestern Iowa","interactions":[],"lastModifiedDate":"2026-03-13T17:07:59.33217","indexId":"ofr20261066","displayToPublicDate":"2026-03-05T11:00:46","publicationYear":"2026","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2026-1066","displayTitle":"Floods of June 2024 in Northwestern Iowa","title":"Floods of June 2024 in northwestern Iowa","docAbstract":"<p>Following a heavy, multiday rainfall event that took place between June 20 and June 22, 2024, widespread flooding occurred in parts of northwestern Iowa. Ten U.S. Geological Survey (USGS) streamgages with periods of record ranging from 56 to 99 years in length experienced new peaks of record, three of which were more than double the previous peak-of-record: 06483500 (Rock River near Rock Valley, Iowa), 06605850 (Little Sioux River at Linn Grove, Iowa), and 06606600 (Little Sioux River at Correctionville, Iowa). A Presidential declaration of a major disaster for the State of Iowa was approved on June 24, 2024, and the cost of the flooding is estimated at over $310 million. The severity of this flooding prompted the USGS, in cooperation with the Iowa Department of Transportation, to summarize the meteorological and hydrological conditions preceding the flooding, compile estimates of the magnitude of peak flows resulting from the flooding, and update estimates of peak-flow frequency for selected USGS streamgages. Of the 33 streamgages analyzed, a peak streamflow occurred that corresponded to an annual exceedance probability of less than 4 percent at 13 streamgages, an annual exceedance probability of less than 1 percent at 6 streamgages, and an annual exceedance probability of less than 0.2 percent at 1 streamgage.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20261066","collaboration":"Prepared in cooperation with the Iowa Department of Transportation","usgsCitation":"Marti, M.K., and O’Shea, P.S., 2026, Floods of June 2024 in northwestern Iowa: U.S. Geological Survey Open-File Report 2026–1066, 16 p., https://doi.org/10.3133/ofr20261066.","productDescription":"Report: vi, 16 p.; Data Release","numberOfPages":"26","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-175807","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":500762,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20261066/full"},{"id":500761,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2026/1066/images/"},{"id":500760,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2026/1066/ofr20261066.XML"},{"id":500759,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2026/1066/ofr20261066.pdf","text":"Report","size":"2.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2026-1066"},{"id":500758,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2026/1066/coverthb.jpg"},{"id":501165,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_119301.htm","linkFileType":{"id":5,"text":"html"}},{"id":500763,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P1JFCNSZ","text":"USGS data release","linkHelpText":"Peak-flow frequency analysis for U.S. Geological Survey streamgages in northwestern Iowa, based on data through water year 2024"}],"country":"United States","state":"Iowa","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -96.667,\n              43.6\n            ],\n            [\n              -96.667,\n              41.667\n            ],\n            [\n              -93,\n              41.667\n            ],\n            [\n              -93,\n              43.6\n            ],\n            [\n              -96.667,\n              43.6\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","contact":"<p>Director, <a href=\"https://www.usgs.gov/centers/cm-water\" data-mce-href=\"https://www.usgs.gov/centers/cm-water\">Central Midwest Water Science Center</a><br>U.S. Geological Survey<br>400 South Clinton Street, Suite 269 <br>Iowa City, Iowa 52240</p><p><a href=\"https://pubs.usgs.gov/contact\" data-mce-href=\"../contact\">Contact Pubs Warehouse</a></p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Purpose and Scope</li><li>U.S. Geological Survey Response to Flood</li><li>Changes in Historical Peak Streamflows</li><li>Summary</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2026-03-05","noUsgsAuthors":false,"publicationDate":"2026-03-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Marti, Mackenzie K. 0000-0001-8817-4969 mmarti@usgs.gov","orcid":"https://orcid.org/0000-0001-8817-4969","contributorId":289738,"corporation":false,"usgs":true,"family":"Marti","given":"Mackenzie","email":"mmarti@usgs.gov","middleInitial":"K.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":956886,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"O’Shea, Padraic S. 0000-0001-9005-8289 poshea@usgs.gov","orcid":"https://orcid.org/0000-0001-9005-8289","contributorId":196742,"corporation":false,"usgs":true,"family":"O’Shea","given":"Padraic","email":"poshea@usgs.gov","middleInitial":"S.","affiliations":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":956887,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70274673,"text":"70274673 - 2026 - Stochastic within-host dynamics and climate-sensitive traits generate predictable patterns of variation in disease outcomes","interactions":[],"lastModifiedDate":"2026-04-03T15:37:07.940747","indexId":"70274673","displayToPublicDate":"2026-03-05T10:32:50","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":23782,"text":"Philosophical Transactions of the Royal Society, Series B","active":true,"publicationSubtype":{"id":10}},"title":"Stochastic within-host dynamics and climate-sensitive traits generate predictable patterns of variation in disease outcomes","docAbstract":"<p><span>Understanding how climatic variables impact host-pathogen relationships in temperature-sensitive ectothermic host organisms is crucial under global change. Few studies have explored how temperature gradients generate inter-individual variation in epidemiological traits like host susceptibility or pathogen replication. Here, we develop a mathematical model to explore a novel hypothesis: stochastic within-host dynamics and simulated thermal mismatches between host and pathogen traits generate predictable variation in infection outcomes among hosts and across thermal gradients. Our model demonstrates that varying trait thermal optima in host immunity and pathogen replication, and stochastic within-host processes produced variation in infection outcomes. Variability was low when temperatures strongly favored host or pathogen traits, but high and diverse when their performance was similar across a broad thermal range. In contrast, when trait performance was equal across all temperatures (no mismatch) variability remained low at all temperatures. Further, the magnitude of variation, quantified by entropy, exhibited predictable patterns depending on host-pathogen thermal mismatches. We conclude that interactions between trait thermal mismatches and within-host stochasticity provide a theoretical framework to improve ectotherm disease models under climate change, providing a valuable tool for exploring the impacts of environmental change on epizootic or epidemic dynamics, particularly in vulnerable marine ecosystems.</span></p>","language":"English","publisher":"Royal Society Publishing","doi":"10.1098/rstb.2024.0328","usgsCitation":"Carlino, A., Loeher, M.M., Páez, D.J., Hershberger, P., Wolf, N., and Mihaljevic, J., 2026, Stochastic within-host dynamics and climate-sensitive traits generate predictable patterns of variation in disease outcomes: Philosophical Transactions of the Royal Society, Series B, v. 381, no. 1945, 20240328, 12 p., https://doi.org/10.1098/rstb.2024.0328.","productDescription":"20240328, 12 p.","ipdsId":"IP-180151","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":502462,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1098/rstb.2024.0328","text":"Publisher Index Page"},{"id":502167,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"381","issue":"1945","noUsgsAuthors":false,"publicationDate":"2026-03-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Carlino, Andrew","contributorId":369232,"corporation":false,"usgs":false,"family":"Carlino","given":"Andrew","affiliations":[{"id":83041,"text":"School of Informatics, Computing, and Cyber Systems, Northern Arizona University, Flagstaff, AZ, USA","active":true,"usgs":false}],"preferred":false,"id":958655,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Loeher, Malina Mariko 0000-0001-9589-5641","orcid":"https://orcid.org/0000-0001-9589-5641","contributorId":365991,"corporation":false,"usgs":true,"family":"Loeher","given":"Malina","middleInitial":"Mariko","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":958656,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Páez, David James 0000-0001-9035-394X","orcid":"https://orcid.org/0000-0001-9035-394X","contributorId":296751,"corporation":false,"usgs":true,"family":"Páez","given":"David","middleInitial":"James","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":958657,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hershberger, Paul 0000-0002-2261-7760","orcid":"https://orcid.org/0000-0002-2261-7760","contributorId":203322,"corporation":false,"usgs":true,"family":"Hershberger","given":"Paul","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":958658,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wolf, Nathan","contributorId":350132,"corporation":false,"usgs":false,"family":"Wolf","given":"Nathan","affiliations":[{"id":12915,"text":"Alaska Pacific University","active":true,"usgs":false}],"preferred":false,"id":958659,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Mihaljevic, Joseph R.","contributorId":352200,"corporation":false,"usgs":false,"family":"Mihaljevic","given":"Joseph R.","affiliations":[{"id":84130,"text":"School of Informatics, Computing, and Cyber Systems, Northern Arizona University, Flagstaff, AZ 86011","active":true,"usgs":false}],"preferred":false,"id":958660,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70274254,"text":"70274254 - 2026 - Fragmentation as a population rate-changer: A field experiment","interactions":[],"lastModifiedDate":"2026-03-23T14:48:49.820811","indexId":"70274254","displayToPublicDate":"2026-03-05T09:20:51","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1465,"text":"Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Fragmentation as a population rate-changer: A field experiment","docAbstract":"<p><span>Experimental and observational studies of effects of fragmentation on biodiversity and population dynamics have produced mixed results, with some reviews concluding strong evidence of negative effects and others concluding small positive effects. In addition, many factors (e.g., interspecific interactions, edge effects, nutrient cycling) have been identified as potential explanations underlying the various results. We carried out a population-level fragmentation study on meadow voles, focusing on changes in vital rates caused by reduced movements in experimental 2-patch systems. We developed predictions of fragmentation effects by decomposing rates of apparent survival and recruitment (parameters directly estimated using capture–recapture models) into components that do and do not include movement. Fragmentation was predicted to reduce movement rates, and reduced movement was predicted to increase apparent survival rates, decrease immigration rates, and slightly increase population growth rates. We found evidence of increased adult and juvenile apparent survival and adult population growth rate on fragmented grids, whereas results for recruitment were ambiguous and did not support our predictions. The recruitment results led to the hypothesis that immigration into suitable habitat may not be reduced by fragmentation as much as permanent emigration from that habitat. A focus on effects of reduced movement on vital rates should be a reasonable starting point for investigations of fragmentation effects. This focus suggests that explanations underlying fragmentation effects will require additional effort devoted to isolating movement components of vital rates.</span></p>","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecy.70327","usgsCitation":"Nichols, J.D., Hines, J.E., Hinz, R.L., and Hinz, J., 2026, Fragmentation as a population rate-changer: A field experiment: Ecology, v. 107, no. 3, e70327, 19 p., https://doi.org/10.1002/ecy.70327.","productDescription":"e70327, 19 p.","ipdsId":"IP-183793","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":501391,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/ja/70274254/images"},{"id":501390,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/ja/70274254/70274254.XML"},{"id":501389,"rank":2,"type":{"id":42,"text":"Open Access USGS Document"},"url":"https://pubs.usgs.gov/publication/70274254/full"},{"id":501388,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"107","issue":"3","noUsgsAuthors":false,"publicationDate":"2026-03-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Nichols, James D. 0000-0002-7631-2890 jnichols@usgs.gov","orcid":"https://orcid.org/0000-0002-7631-2890","contributorId":200533,"corporation":false,"usgs":true,"family":"Nichols","given":"James","email":"jnichols@usgs.gov","middleInitial":"D.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":957200,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hines, James E. 0000-0001-5478-7230 jhines@usgs.gov","orcid":"https://orcid.org/0000-0001-5478-7230","contributorId":146530,"corporation":false,"usgs":true,"family":"Hines","given":"James","email":"jhines@usgs.gov","middleInitial":"E.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":957201,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hinz, Robert L.","contributorId":43454,"corporation":false,"usgs":true,"family":"Hinz","given":"Robert","email":"","middleInitial":"L.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":957202,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hinz, Janet","contributorId":367241,"corporation":false,"usgs":false,"family":"Hinz","given":"Janet","affiliations":[],"preferred":false,"id":957203,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
]}