{"pageNumber":"3","pageRowStart":"50","pageSize":"25","recordCount":10445,"records":[{"id":70274638,"text":"70274638 - 2025 - Postglacial eruptive history of Laguna del Maule volcanic field and constraints on its magmatic system","interactions":[],"lastModifiedDate":"2026-04-02T17:42:17.826154","indexId":"70274638","displayToPublicDate":"2025-12-15T10:33:19","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2462,"text":"Journal of South American Earth Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Postglacial eruptive history of Laguna del Maule volcanic field and constraints on its magmatic system","docAbstract":"<p><span id=\"_mce_caret\" data-mce-bogus=\"1\" data-mce-type=\"format-caret\"><span>The Laguna del Maule (LdM) volcanic field has produced &gt;100 explosive and extrusive events over the past 17 ka. More than two-thirds of these have been silicic, with most being postglacial rhyolites (72–78&nbsp;% SiO</span><sub>2</sub><span>) concentrated near the eponymous lake (LdM), an extraordinary anomaly in the Quaternary Andes and unprecedented in this 1.5–Ma-old volcanic field as a whole. The postglacial field includes &gt;70 separate vents distributed over ∼360&nbsp;km</span><sup>2</sup><span>&nbsp;that together produced the many distinct eruptive events, of which 55 are rhyolitic (73&nbsp;%−77&nbsp;% SiO</span><sub>2</sub><span>), 18 are rhyodacitic (68&nbsp;%−72&nbsp;% SiO</span><sub>2</sub><span>), 4 are dacitic (63&nbsp;%–66&nbsp;% SiO</span><sub>2</sub><span>), 26 are intermediate (54–62&nbsp;% SiO</span><sub>2</sub><span>), and 2 are true basalts (50&nbsp;%–53&nbsp;% SiO</span><sub>2</sub><span>). Of these, most originated from single-vent domes, cones, or craters that erupted effusive and/or explosive products, each with relatively short lifespans. Some originated from multi-vent centers, the largest one being the Barrancas complex southeast of the lake, which has as many as 18 vents that erupted over as much as 10 kyr. The LdM basin itself is ringed by 13 separate silicic centers, many of which are also multi-vent and built over time by multiple explosive and extrusive events. These surround the lake, near the middle of which is the vent for the high-silica rhyolite Plinian eruption that produced the “</span><i>Rhyolite of Laguna del Maule</i><span>”, which was the first and largest silicic event from the postglacial field. Explosive and effusive products from all these events have been put in a time-stratigraphic framework supported by radiocarbon dating and chemical analyses to reconstruct the postglacial eruptive history. Correlations of pyroclastics to eruptive vents have provided a spatial-temporal framework that helps characterize the magmatic system beneath the LdM field. Distribution of both silicic and mafic vents support the likelihood that two separate magmatic systems produced the postglacial eruptions in the volcanic field—one in the Laguna del Maule basin and the other at the Barrancas complex—with a cluster of silicic vents at each and mafic vents situated between the two. Vent distributions, compositions of eruptive products, and temporal and spatial trends of eruptive units suggest that the abundant rhyodacitic and mafic units in the LdM basin have no common magma reservoir, but instead each had its own evolutionary trend. In contrast, there is enough affinity among some of the rhyolitic units in the Basin to imply magmatic connections and/or continuity that span both time and space, although neither geographic proximity nor temporal similarity have singular control on LdM-basin rhyolite compositions. Compositional trends through time at the Barrancas center suggest the rhyolitic eruptions at West and East Barrancas were derived from separate, zoned reservoirs that were tapped in batches, not permitting development of a large high-silica reservoir such as that beneath the LdM basin.</span></span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jsames.2025.105813","usgsCitation":"Fierstein, J., Sruoga, P., Amigo, A., Elissondo, M., and Rosas, M., 2025, Postglacial eruptive history of Laguna del Maule volcanic field and constraints on its magmatic system: Journal of South American Earth Sciences, v. 168, 105813, 40 p., https://doi.org/10.1016/j.jsames.2025.105813.","productDescription":"105813, 40 p.","ipdsId":"IP-174310","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":502019,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Argentina, Chile","otherGeospatial":"Laguna del Maule lake basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -70.59545505016834,\n              -35.97940016009683\n            ],\n            [\n              -70.59545505016834,\n              -36.12055654053491\n            ],\n            [\n              -70.3551914157175,\n              -36.12055654053491\n            ],\n            [\n              -70.3551914157175,\n              -35.97940016009683\n            ],\n            [\n              -70.59545505016834,\n              -35.97940016009683\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"168","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Fierstein, Judith 0000-0001-8024-1426 jfierstn@usgs.gov","orcid":"https://orcid.org/0000-0001-8024-1426","contributorId":147000,"corporation":false,"usgs":true,"family":"Fierstein","given":"Judith","email":"jfierstn@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":958509,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sruoga, Patricia","contributorId":369133,"corporation":false,"usgs":false,"family":"Sruoga","given":"Patricia","affiliations":[{"id":87728,"text":"SEGEMAR, Argentina","active":true,"usgs":false}],"preferred":false,"id":958510,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Amigo, Alvaro","contributorId":369134,"corporation":false,"usgs":false,"family":"Amigo","given":"Alvaro","affiliations":[{"id":82689,"text":"SERNAGEOMIN, Chile","active":true,"usgs":false}],"preferred":false,"id":958511,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Elissondo, Manuela","contributorId":345642,"corporation":false,"usgs":false,"family":"Elissondo","given":"Manuela","email":"","affiliations":[{"id":82670,"text":"Servicio Geológico Minero Argentino (SEGEMAR), Buenos Aires, Argentina","active":true,"usgs":false}],"preferred":false,"id":958512,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rosas, Mario","contributorId":369135,"corporation":false,"usgs":false,"family":"Rosas","given":"Mario","affiliations":[{"id":87728,"text":"SEGEMAR, Argentina","active":true,"usgs":false}],"preferred":false,"id":958513,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70274190,"text":"70274190 - 2025 - Advancements in satellite observations of inland and coastal waters: Building towards a global validation network","interactions":[],"lastModifiedDate":"2026-03-04T22:19:21.237913","indexId":"70274190","displayToPublicDate":"2025-12-11T15:12:19","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Advancements in satellite observations of inland and coastal waters: Building towards a global validation network","docAbstract":"The use of satellite-based remote sensing imagery for water quality monitoring of inland and coastal waters has become widespread over the last few decades, with the expansion of, and investment in, operational Earth-observing missions. Satellite-based sensors are uniquely suited to provide synoptic, system-wide water quality parameter estimates that supplement traditional field-based sampling methods. The remote sensing of water quality parameter estimates is particularly valuable in systems with high temporal and spatial variability, as well as in areas that are difficult to access, or where agencies lack funding for routine monitoring. However, optically complex inland and coastal waters pose additional challenges for developing robust remote sensing retrieval models for optical properties and water quality parameters. One of the biggest challenges is collecting high quality field measurements that are used to calibrate and validate the retrieval algorithms. Here, we present the current status of satellite missions, field methods that include instruments used and commonly measured parameters, and repositories of historical field data that are relevant to inland and coastal water studies. We then present data requirements for model validation and highlight gaps in validation coverage. Finally, we provide suggestions for future field campaigns to improve coordination with remote sensing data collection and to ensure that field data is well suited for use in model or algorithm development.","language":"English","publisher":"Multidisciplinary Digital Publishing Institute (MDPI)","doi":"10.3390/rs17244008","usgsCitation":"Avouris, D., Maciel, F., Sharp, S.L., Craig, S.E., Dekker, A.G., Di Vittorio, C.A., Gardner, J.R., Goldsmith, E.C., Gossn, J.I., Greb, S.R., Grunert, B.K., Gurlin, D., Jampani, M., Khan, R.M., Lowin, B., McKinna, L., Mouw, C.B., Ogashawara, I., Rivero Calle, S., Salls, W.B., Sanchez-Cabeza, J., Schaeffer, B., Seegers, B.N., Silander, J., Smail, E.A., Wang, M., and Werdell, P.J., 2025, Advancements in satellite observations of inland and coastal waters: Building towards a global validation network: Remote Sensing, v. 17, no. 24, 4008, 37 p., https://doi.org/10.3390/rs17244008.","productDescription":"4008, 37 p.","ipdsId":"IP-170154","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":500849,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs17244008","text":"Publisher Index Page"},{"id":500767,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"17","issue":"24","noUsgsAuthors":false,"publicationDate":"2025-12-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Avouris, Dulcinea Marie 0000-0001-5797-3960","orcid":"https://orcid.org/0000-0001-5797-3960","contributorId":335170,"corporation":false,"usgs":true,"family":"Avouris","given":"Dulcinea Marie","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":956852,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Maciel, Fernanda 0000-0003-3872-1121","orcid":"https://orcid.org/0000-0003-3872-1121","contributorId":367146,"corporation":false,"usgs":false,"family":"Maciel","given":"Fernanda","affiliations":[{"id":87566,"text":"Instituto de Mecánica de los Fluidos e Ingeniería Ambiental, Facultad de Ingeniería, Universidad de la República, Uruguay","active":true,"usgs":false}],"preferred":false,"id":956853,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sharp, Samantha L. 0000-0002-9297-2004","orcid":"https://orcid.org/0000-0002-9297-2004","contributorId":367147,"corporation":false,"usgs":false,"family":"Sharp","given":"Samantha","middleInitial":"L.","affiliations":[{"id":87567,"text":"University of California, Davis, USA","active":true,"usgs":false}],"preferred":false,"id":956854,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Craig, Susanne E. 0000-0002-8963-0951","orcid":"https://orcid.org/0000-0002-8963-0951","contributorId":367148,"corporation":false,"usgs":false,"family":"Craig","given":"Susanne","middleInitial":"E.","affiliations":[{"id":87568,"text":"NASA Goddard Space Flight Center/GESTAR II University of Baltimore County, USA","active":true,"usgs":false}],"preferred":false,"id":956855,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dekker, Arnold G. 0000-0002-8160-6498","orcid":"https://orcid.org/0000-0002-8160-6498","contributorId":367149,"corporation":false,"usgs":false,"family":"Dekker","given":"Arnold","middleInitial":"G.","affiliations":[{"id":87569,"text":"CSIRO (Commonwealth Scientific Industrial Research Organisation), Australia","active":true,"usgs":false}],"preferred":false,"id":956856,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Di Vittorio, Courtney A. 0000-0001-8623-1982","orcid":"https://orcid.org/0000-0001-8623-1982","contributorId":367150,"corporation":false,"usgs":false,"family":"Di Vittorio","given":"Courtney","middleInitial":"A.","affiliations":[{"id":87570,"text":"Wake Forest University, Engineering Department, USA","active":true,"usgs":false}],"preferred":false,"id":956857,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Gardner, John R. 0000-0002-1454-5074","orcid":"https://orcid.org/0000-0002-1454-5074","contributorId":367151,"corporation":false,"usgs":false,"family":"Gardner","given":"John","middleInitial":"R.","affiliations":[{"id":87571,"text":"University of Pittsburgh, Department of Geology and Environmental Science, USA","active":true,"usgs":false}],"preferred":false,"id":956858,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Goldsmith, Emma C. 0000-0003-0029-0952","orcid":"https://orcid.org/0000-0003-0029-0952","contributorId":367152,"corporation":false,"usgs":false,"family":"Goldsmith","given":"Emma","middleInitial":"C.","affiliations":[{"id":87572,"text":"Skidaway Institute of Oceanography, University of Georgia, USA \nCreighton University, USA\nBAE Systems Inc. Space & Mission Systems, USA","active":true,"usgs":false}],"preferred":false,"id":956859,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Gossn, Juan I. 0000-0001-9277-6882","orcid":"https://orcid.org/0000-0001-9277-6882","contributorId":367153,"corporation":false,"usgs":false,"family":"Gossn","given":"Juan","middleInitial":"I.","affiliations":[{"id":87573,"text":"European Agency for the Exploitation of Meteorological Satellites, Germany","active":true,"usgs":false}],"preferred":false,"id":956860,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Greb, Steven R. 0000-0002-9028-0055","orcid":"https://orcid.org/0000-0002-9028-0055","contributorId":367154,"corporation":false,"usgs":false,"family":"Greb","given":"Steven","middleInitial":"R.","affiliations":[{"id":87574,"text":"University of Wisconsin-Madison, USA","active":true,"usgs":false}],"preferred":false,"id":956861,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Grunert, Brice K. 0000-0002-6951-1701","orcid":"https://orcid.org/0000-0002-6951-1701","contributorId":367155,"corporation":false,"usgs":false,"family":"Grunert","given":"Brice","middleInitial":"K.","affiliations":[{"id":87575,"text":"Cleveland State University, USA","active":true,"usgs":false}],"preferred":false,"id":956862,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Gurlin, Daniela","contributorId":267807,"corporation":false,"usgs":false,"family":"Gurlin","given":"Daniela","email":"","affiliations":[],"preferred":false,"id":956863,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Jampani, Mahesh 0000-0002-8925-719X","orcid":"https://orcid.org/0000-0002-8925-719X","contributorId":367156,"corporation":false,"usgs":false,"family":"Jampani","given":"Mahesh","affiliations":[{"id":87576,"text":"International Water Management Institute (IWMI-CGIAR), Colombo, Sri Lanka","active":true,"usgs":false}],"preferred":false,"id":956864,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Khan, Rabia M. 0000-0001-6715-5910","orcid":"https://orcid.org/0000-0001-6715-5910","contributorId":367157,"corporation":false,"usgs":false,"family":"Khan","given":"Rabia","middleInitial":"M.","affiliations":[{"id":87577,"text":"State University of New York - College of Environmental Science and Forestry, USA","active":true,"usgs":false}],"preferred":false,"id":956865,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Lowin, Ben 0000-0001-5826-7216","orcid":"https://orcid.org/0000-0001-5826-7216","contributorId":367158,"corporation":false,"usgs":false,"family":"Lowin","given":"Ben","affiliations":[{"id":87578,"text":"Skidaway Institute of Oceanography and the University of Georgia, USA","active":true,"usgs":false}],"preferred":false,"id":956866,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"McKinna, Lachlan 0000-0001-6986-8121","orcid":"https://orcid.org/0000-0001-6986-8121","contributorId":367159,"corporation":false,"usgs":false,"family":"McKinna","given":"Lachlan","affiliations":[{"id":87579,"text":"1GO2Q PTY LTD, Sunshine Coast, QLD, Australia\n2NASA GSFC, Code 616, Greenbelt, MD, USA","active":true,"usgs":false}],"preferred":false,"id":956867,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Mouw, Colleen B. 0000-0003-2516-1882","orcid":"https://orcid.org/0000-0003-2516-1882","contributorId":367160,"corporation":false,"usgs":false,"family":"Mouw","given":"Colleen","middleInitial":"B.","affiliations":[{"id":87580,"text":"University of Rhode Island, Graduate School of Oceanography, Narragansett, RI, USA","active":true,"usgs":false}],"preferred":false,"id":956868,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Ogashawara, Igor 0000-0001-6328-0001","orcid":"https://orcid.org/0000-0001-6328-0001","contributorId":367161,"corporation":false,"usgs":false,"family":"Ogashawara","given":"Igor","affiliations":[{"id":87581,"text":"Department of Plankton and Microbial Ecology, Leibniz Institute of Freshwater Ecology and Inland Fisheries, Germany","active":true,"usgs":false}],"preferred":false,"id":956869,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Rivero Calle, Sara 0000-0002-7538-0429","orcid":"https://orcid.org/0000-0002-7538-0429","contributorId":367162,"corporation":false,"usgs":false,"family":"Rivero Calle","given":"Sara","affiliations":[{"id":87578,"text":"Skidaway Institute of Oceanography and the University of Georgia, USA","active":true,"usgs":false}],"preferred":false,"id":956870,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Salls, Wilson B. 0000-0001-7505-0828","orcid":"https://orcid.org/0000-0001-7505-0828","contributorId":260858,"corporation":false,"usgs":false,"family":"Salls","given":"Wilson","email":"","middleInitial":"B.","affiliations":[{"id":37230,"text":"EPA","active":true,"usgs":false}],"preferred":false,"id":956871,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Sanchez-Cabeza, Joan-Albert","contributorId":346065,"corporation":false,"usgs":false,"family":"Sanchez-Cabeza","given":"Joan-Albert","email":"","affiliations":[{"id":82761,"text":"CIMAT","active":true,"usgs":false}],"preferred":false,"id":956872,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Schaeffer, Blake 0000-0001-9794-3977","orcid":"https://orcid.org/0000-0001-9794-3977","contributorId":245603,"corporation":false,"usgs":false,"family":"Schaeffer","given":"Blake","email":"","affiliations":[{"id":37230,"text":"EPA","active":true,"usgs":false}],"preferred":false,"id":956873,"contributorType":{"id":1,"text":"Authors"},"rank":22},{"text":"Seegers, Bridget N. 0000-0003-3657-632X","orcid":"https://orcid.org/0000-0003-3657-632X","contributorId":367163,"corporation":false,"usgs":false,"family":"Seegers","given":"Bridget","middleInitial":"N.","affiliations":[{"id":87582,"text":"Morgan State University, Baltimore, MD, USA And NASA Goddard Space Flight Center, USA","active":true,"usgs":false}],"preferred":false,"id":956874,"contributorType":{"id":1,"text":"Authors"},"rank":23},{"text":"Silander, Jari 0000-0001-7408-7047","orcid":"https://orcid.org/0000-0001-7408-7047","contributorId":367164,"corporation":false,"usgs":false,"family":"Silander","given":"Jari","affiliations":[{"id":87584,"text":"Finnish Environmental Institute, Uusimaa, Finland","active":true,"usgs":false}],"preferred":false,"id":956875,"contributorType":{"id":1,"text":"Authors"},"rank":24},{"text":"Smail, Emily A. 0000-0003-0613-4555","orcid":"https://orcid.org/0000-0003-0613-4555","contributorId":367165,"corporation":false,"usgs":false,"family":"Smail","given":"Emily","middleInitial":"A.","affiliations":[{"id":87585,"text":"Science Systems and Applications, Inc., USA","active":true,"usgs":false}],"preferred":false,"id":956876,"contributorType":{"id":1,"text":"Authors"},"rank":25},{"text":"Wang, Menghua 0000-0001-7019-3125","orcid":"https://orcid.org/0000-0001-7019-3125","contributorId":367166,"corporation":false,"usgs":false,"family":"Wang","given":"Menghua","affiliations":[{"id":87586,"text":"NOAA Center for Satellite Applications and Research, College Park, MD, USA","active":true,"usgs":false}],"preferred":false,"id":956877,"contributorType":{"id":1,"text":"Authors"},"rank":26},{"text":"Werdell, P. Jeremy 0000-0002-3592-0152","orcid":"https://orcid.org/0000-0002-3592-0152","contributorId":222358,"corporation":false,"usgs":false,"family":"Werdell","given":"P.","email":"","middleInitial":"Jeremy","affiliations":[{"id":38788,"text":"NASA","active":true,"usgs":false}],"preferred":false,"id":956878,"contributorType":{"id":1,"text":"Authors"},"rank":27}]}}
,{"id":70273827,"text":"70273827 - 2025 - Streamflow as a stressor: Disentangling hydrology and water quality impacts to characterize flow-ecology relationships for two stream assemblages across two southeastern landscapes","interactions":[],"lastModifiedDate":"2026-02-06T14:18:06.984716","indexId":"70273827","displayToPublicDate":"2025-12-11T10:01:58","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1447,"text":"Ecohydrology","active":true,"publicationSubtype":{"id":10}},"title":"Streamflow as a stressor: Disentangling hydrology and water quality impacts to characterize flow-ecology relationships for two stream assemblages across two southeastern landscapes","docAbstract":"<p><span>Disassociating the independent effects of flow and water quality on the ecology of flowing waters is an overarching goal in water resource science needed to improve the efficacy of watershed management. However, the interrelatedness of these gradients and their subsequent alteration due to land use change has constrained progress made on this front. The objective of this study was to use benthic macroinvertebrate and fish assemblage data to characterize flow-ecology relationships that were unchanged by water quality impacts across two southeastern landscapes in the USA to help detect ecological change driven by flow alteration. General linear latent models were used to identify taxa that were responsive to high or low flow metrics and water quality gradients. Bayesian hierarchical generalized additive models were then developed using these indicator taxa and three biological metrics to identify flow-specific relationships that were unaffected by water quality impacts. Three low flow-specific relationships were identified, illustrating how potential agricultural or urban impacts to hydrology reduced stream biological health. Importantly, flow-ecology relationships developed using indicator taxa in this study effectively captured hydrology-specific impacts while biological metrics typical of state monitoring and assessment programs did not. Therefore, developing flow-specific biological metrics is a critical step when developing management strategies targeting flow alteration. Implementing standardized frameworks such as the one characterized here can limit contradictory findings and improve streamflow enhancement and restoration project efficacy. These low flow-specific relationships will enhance managers' capacity to develop environmental flow standards, monitor their success, and better understand urban and agricultural impacts on stream assemblages.</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/eco.70129","usgsCitation":"Hubbell, J., 2025, Streamflow as a stressor: Disentangling hydrology and water quality impacts to characterize flow-ecology relationships for two stream assemblages across two southeastern landscapes: Ecohydrology, v. 18, no. 8, e70129, 19 p., https://doi.org/10.1002/eco.70129.","productDescription":"e70129, 19 p.","ipdsId":"IP-170276","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":499585,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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 \"}}]}","volume":"18","issue":"8","noUsgsAuthors":false,"publicationDate":"2025-12-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Hubbell, Joshua Paul 0000-0002-5455-8451","orcid":"https://orcid.org/0000-0002-5455-8451","contributorId":347668,"corporation":false,"usgs":true,"family":"Hubbell","given":"Joshua Paul","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":955110,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70272794,"text":"70272794 - 2025 - Summary of first daily ring formation in otoliths of freshwater fishes in the continental United States","interactions":[],"lastModifiedDate":"2025-12-09T15:56:06.687488","indexId":"70272794","displayToPublicDate":"2025-12-02T08:49:00","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1657,"text":"Fisheries","onlineIssn":"1548-8446","printIssn":"0363-2415","active":true,"publicationSubtype":{"id":10}},"title":"Summary of first daily ring formation in otoliths of freshwater fishes in the continental United States","docAbstract":"<p><span id=\"_mce_caret\" data-mce-bogus=\"1\" data-mce-type=\"format-caret\"><span>Daily ring counts in young-of-the-year fishes are important for estimating important vital rates, such as growth, mortality, and timing of hatch. To accurately estimate some of these rates, the timing of the first daily ring must be estimated accurately. Variation in the timing of&nbsp;the first daily ring can be attributed to many factors, including biology of the species and experience of laboratory personnel. The amount of variation and the degree of differences, however, have not been quantified, hindering the utility of daily ring information to provide accurate estimates of spawning and hatching times. We conducted a review of studies for freshwater fishes in the continental United States to quantify variation in daily ring validation studies as it relates to timing of the first ring. We found 40 studies representing 12 orders, 15&nbsp;families, and 35 species. Most studies investigated rings in the sagittae, although the lapilli and asterisci were also used for a few species. Variation in the timing of the first ring formation was evident, but not consistent among otolith types or groups of fishes. The first daily ring in sagittae varied from 31 d before hatch to 150 d after hatch. First daily ring formation in lapilli was consistent within families but formed before hatch in some families of fish and after hatch in other families. The first daily ring in asterisci were near universally formed after hatch, with the exception of one species of sturgeon (family Acipenseridae). Only three of the nine species where replicate studies existed were found to exhibit consistent first ring formation timing. Such findings suggest that differences among laboratories and personnel may play a larger role than differences among species or populations when inconsistent first ring formation timing results occur. For most species, error surrounding differences in timing formation is about 1 week, except for Salmoniformes, where error was up to a 150-d difference. Incorporating species biology along with uncertainty in temporal estimates based on otolith chronology would aid interpretation of results in field situations.</span></span></p>","language":"English","publisher":"Oxford Academic","doi":"10.1093/fshmag/vuaf097","usgsCitation":"Long, J.M., and Snow, R.A., 2025, Summary of first daily ring formation in otoliths of freshwater fishes in the continental United States: Fisheries, vuaf097, https://doi.org/10.1093/fshmag/vuaf097.","productDescription":"vuaf097","ipdsId":"IP-170212","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":497282,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"continental United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"geometry\": {\n        \"type\": \"MultiPolygon\",\n        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Atlanta","active":true,"usgs":true}],"preferred":true,"id":951796,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Snow, Richard A.","contributorId":264712,"corporation":false,"usgs":false,"family":"Snow","given":"Richard","middleInitial":"A.","affiliations":[{"id":27443,"text":"Oklahoma Department of Wildlife Conservation","active":true,"usgs":false}],"preferred":false,"id":951797,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70272697,"text":"70272697 - 2025 - Estimation of dynamic geologic CO2 storage resources in the Illinois Basin, including effects of brine extraction, anisotropy, and hydrogeologic heterogeneity","interactions":[],"lastModifiedDate":"2025-12-04T16:26:55.8147","indexId":"70272697","displayToPublicDate":"2025-12-01T10:13:31","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5232,"text":"Frontiers in Earth Science","onlineIssn":"2296-6463","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Estimation of dynamic geologic CO<sub>2</sub> storage resources in the Illinois Basin, including effects of brine extraction, anisotropy, and hydrogeologic heterogeneity","title":"Estimation of dynamic geologic CO2 storage resources in the Illinois Basin, including effects of brine extraction, anisotropy, and hydrogeologic heterogeneity","docAbstract":"<p><span>Since the vast majority of carbon dioxide (CO</span><sub>2</sub><span>) storage resources in the United States are in deep saline aquifers, optimizing the use of these saline storage resources could be crucial for efficient development of geologic CO</span><sub>2</sub><span>&nbsp;storage (GCS) resources and basin- or larger-scale deployment of GCS in the country. Maximum CO</span><sub>2</sub><span>&nbsp;injection rates can be enhanced by extracting brine from the CO</span><sub>2</sub><span>&nbsp;storage unit. However, disposal of the extracted brine is both a technological and economic challenge. The lowest-cost option would likely be reinjection of the extracted brine into another formation above or below the CO</span><sub>2</sub><span>&nbsp;storage unit. Therefore, it is important to estimate brine injectivity as it will constrain the potential to increase CO</span><sub>2</sub><span>&nbsp;injectivity at an injection site that has access to multiple geologic storage units where either CO</span><sub>2</sub><span>&nbsp;or brine can be injected. Using a simulation-optimization framework, coupled with a non-isothermal, multiphase CO</span><sub>2</sub><span>-water-salt equation-of-state module, we developed a computationally efficient method for evaluating optimization of simultaneous CO</span><sub>2</sub><span>&nbsp;injection, brine extraction, and brine (re)injection at hypothetical injection sites deployed across a geologic basin. The Illinois basin is ideal for testing our methodology because it contains multiple geologic storage units with seals in between them to isolate injection of CO</span><sub>2</sub><span>&nbsp;in one unit from interfering with the injection of either brine or CO</span><sub>2</sub><span>&nbsp;in another unit above or below it. In addition, we investigated the relative effects of variation in key geologic parameters as well as two reservoir structures (hydrogeologic heterogeneity/anisotropy and homogeneity/isotropy) on CO</span><sub>2</sub><span>&nbsp;injectivities and enhancement of CO</span><sub>2</sub><span>&nbsp;injectivity through extracting brine. Results suggest that permeability, depth, and especially thickness of the storage unit could be the most influential parameters determining CO</span><sub>2</sub><span>&nbsp;injectivity. They also suggest that only injecting CO</span><sub>2</sub><span>&nbsp;into the storage unit with the greatest injectivity, enhancing that unit’s injectivity by extracting brine, and disposing of the produced brine in other suitable units could maximize total CO</span><sub>2</sub><span>&nbsp;injectivity in limited regions of the basin. At the majority of simulated injection sites, however, we found that injecting CO</span><sub>2</sub><span>&nbsp;into all of the accessible and suitable storage units was more likely to maximize the CO</span><sub>2</sub><span>&nbsp;storage resource.</span></p>","language":"English","publisher":"Frontiers Media","doi":"10.3389/feart.2025.1639952","usgsCitation":"Plampin, M.R., Anderson, S.T., Finsterle, S., and Wiens, A.M., 2025, Estimation of dynamic geologic CO2 storage resources in the Illinois Basin, including effects of brine extraction, anisotropy, and hydrogeologic heterogeneity: Frontiers in Earth Science, v. 13, 1639952, 18 p., https://doi.org/10.3389/feart.2025.1639952.","productDescription":"1639952, 18 p.","ipdsId":"IP-177734","costCenters":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":497113,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/feart.2025.1639952","text":"Publisher Index Page"},{"id":497059,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Illinois, Kentucky, Indiana","otherGeospatial":"Illinois Basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -91.66105038187163,\n              41.36771728120675\n            ],\n            [\n              -91.66105038187163,\n              37.13535863641968\n            ],\n            [\n              -84.79728409671057,\n              37.13535863641968\n            ],\n            [\n              -84.79728409671057,\n              41.36771728120675\n            ],\n            [\n              -91.66105038187163,\n              41.36771728120675\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"13","noUsgsAuthors":false,"publicationDate":"2025-12-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Plampin, Michelle R. 0000-0003-4068-5801","orcid":"https://orcid.org/0000-0003-4068-5801","contributorId":363249,"corporation":false,"usgs":false,"family":"Plampin","given":"Michelle","middleInitial":"R.","affiliations":[{"id":86662,"text":"USGS, Geology, Energy & Minerals Science Center, DRP not in active directory","active":true,"usgs":false}],"preferred":false,"id":951354,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Anderson, Steven T. 0000-0003-3481-3424 sanderson@usgs.gov","orcid":"https://orcid.org/0000-0003-3481-3424","contributorId":2532,"corporation":false,"usgs":true,"family":"Anderson","given":"Steven","email":"sanderson@usgs.gov","middleInitial":"T.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":951355,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Finsterle, Stefan","contributorId":299677,"corporation":false,"usgs":false,"family":"Finsterle","given":"Stefan","email":"","affiliations":[{"id":64929,"text":"Finsterle GeoConsulting, Inc.","active":true,"usgs":false}],"preferred":false,"id":951356,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wiens, Ashton M. 0000-0002-7030-0602","orcid":"https://orcid.org/0000-0002-7030-0602","contributorId":271176,"corporation":false,"usgs":true,"family":"Wiens","given":"Ashton","email":"","middleInitial":"M.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":951357,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70273143,"text":"70273143 - 2025 - Pre-eruptive characteristics of “suspect” silicic magmas in Carlin-type Au-forming systems","interactions":[],"lastModifiedDate":"2025-12-16T15:37:04.093312","indexId":"70273143","displayToPublicDate":"2025-12-01T09:31:24","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":738,"text":"American Mineralogist","active":true,"publicationSubtype":{"id":10}},"title":"Pre-eruptive characteristics of “suspect” silicic magmas in Carlin-type Au-forming systems","docAbstract":"<p><span>World-class Carlin-type Au deposits hosted in sedimentary rock were formed when profuse Eocene silicic magmatism swept across northern Nevada in response to arc migration. Carlin-type Au deposits formed along with porphyry/skarn Cu-Mo-W-Au deposits, epithermal Ag-Au deposits, and distal disseminated Ag-Au deposits. But unlike these other Au-bearing deposits that have clear associations with igneous intrusions, Carlin-type ore deposits appear to have formed distant from concealed plutons, and their origin remains controversial. Despite decades of abundant geophysical, geochronological, and geochemical studies suggesting the involvement of magmas, concrete evidence for magmatic involvement is still lacking. Consequently, the involvement of contemporaneous igneous systems remains inferred based on age, proximity, and variable isotopic, geochemical, and geophysical clues. A recent synthesis of deposit models postulates that Carlin-type Au deposits are intrusion-related, but that the causative magmas reside deeper (∼6–12&nbsp;km) than in typical porphyry and peripheral systems (∼3–5&nbsp;km), meaning that Carlin-type deposits are perhaps more distal expressions of igneous intrusions. We investigate a collection of “suspect” magmatic systems over a ∼7&nbsp;m.y. timespan (∼41–34 Ma) that are contemporaneous with and near known Carlin-type ore deposits. We report results of a multifaceted array of in situ geochemical analyses (FTIR, EMP, SHRIMP-RG, LA-ICP-MS) of quartz-hosted melt inclusions, biotite, and quartz to better characterize the pre-eruptive characteristics of these magmas. We also report results of thermobarometry and thermodynamic phase equilibria modeling to help place constraints on magmatic reservoir depths and processes. Rather than a single “flavor” of silicic magma, we observe a surprisingly broad compositional spectrum of rhyolites, with one end of the spectrum exhibiting more arc-like (I-type) characteristics and the other end displaying more post-subduction, thick-crust extensional (A-type) characteristics. This broad compositional spectrum suggests a more complex picture of silicic crustal magmatism operating over a narrow span of time during slab rollback. Despite this spectrum, magmatic systems in this study are consistently ferroan and generally peraluminous, which we interpret as an expression of the relatively elevated geotherm at the time and incorporation of variable amounts of highly peraluminous metasedimentary crustal components. The silicic magma spectrum encompasses a range of mineralization associations, including subduction-related Cu-Mo-W-Au-Ag and post-subduction, thick-crust extensional rare-metal Mo-Sn-W-F-Be-Ag-Au, consistent with the prolific and diverse array of ore deposits that formed during this time. Carlin-type Au deposition appears to be associated with nearly the entire magmatic spectrum. This apparent indifference to silicic magma “flavor” would seem to imply that if magmas are involved in Carlin-type Au deposit genesis, they perhaps do not need to be compositionally specialized and/or possibly are only relevant as heat sources driving circulation to remobilize and redistribute metals.</span></p>","language":"English","publisher":"Mineralogical Society of America","doi":"10.2138/am-2024-9372","usgsCitation":"Mercer, C.N., Roberge, J., Khoury, R., and Hofstra, A.H., 2025, Pre-eruptive characteristics of “suspect” silicic magmas in Carlin-type Au-forming systems: American Mineralogist, v. 110, no. 2, p. 1898-1918, https://doi.org/10.2138/am-2024-9372.","productDescription":"21 p.","startPage":"1898","endPage":"1918","ipdsId":"IP-097749","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":497571,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nevada","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -120,\n              42\n            ],\n            [\n              -120,\n              38\n            ],\n            [\n              -114,\n              38\n            ],\n            [\n              -114,\n              42\n            ],\n            [\n              -120,\n              42\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"110","issue":"2","noUsgsAuthors":false,"publicationDate":"2025-12-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Mercer, Celestine N. 0000-0001-8359-4147 cmercer@usgs.gov","orcid":"https://orcid.org/0000-0001-8359-4147","contributorId":4006,"corporation":false,"usgs":true,"family":"Mercer","given":"Celestine","email":"cmercer@usgs.gov","middleInitial":"N.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":952438,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Roberge, Julie","contributorId":152268,"corporation":false,"usgs":false,"family":"Roberge","given":"Julie","email":"","affiliations":[{"id":18893,"text":"Instituto Politecnico Nacional, ESIA-Ticoman","active":true,"usgs":false}],"preferred":false,"id":952439,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Khoury, Regina Marie 0000-0003-2421-986X","orcid":"https://orcid.org/0000-0003-2421-986X","contributorId":294769,"corporation":false,"usgs":true,"family":"Khoury","given":"Regina Marie","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":952440,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hofstra, Albert H. 0000-0002-2450-1593 ahofstra@usgs.gov","orcid":"https://orcid.org/0000-0002-2450-1593","contributorId":1302,"corporation":false,"usgs":true,"family":"Hofstra","given":"Albert","email":"ahofstra@usgs.gov","middleInitial":"H.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":952441,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70272971,"text":"70272971 - 2025 - Leveraging an observed-data likelihood improves the use of machine learning labels in a Bayesian hierarchical model for bioacoustic data","interactions":[],"lastModifiedDate":"2025-12-11T14:50:29.76691","indexId":"70272971","displayToPublicDate":"2025-12-01T08:41:50","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":787,"text":"Annals of Applied Statistics","active":true,"publicationSubtype":{"id":10}},"title":"Leveraging an observed-data likelihood improves the use of machine learning labels in a Bayesian hierarchical model for bioacoustic data","docAbstract":"<p><span>Classification of massive datasets by machine learning (ML) algorithms is promising for many scientific domains, especially wildlife monitoring programs that rely on passive acoustic surveys for detecting species. However, treating ML-predicted class labels (e.g., species identity) as truth biases inferences of focal parameters within common modeling frameworks. One solution is to model the misclassification process explicitly using human-validated true-class labels for a subset of observations. Validation by experts can present a substantial bottleneck in otherwise efficient workflows that use ML predictions. Bioacoustics practitioners seek guidance on both the quantity and process for selecting ML-labeled data to validate by an expert. We derive an alternative model formulation that jointly models human-validated and ML-predicted class labels with an observed-data likelihood (ODL) and use empirically informed simulations motivated by a real-data application to explore different probability designs for selecting class labels for validation. Simulation results suggest that with smaller validation sets the ODL formulation increases computational speed and reduces estimation error compared to a default MCMC data augmentation routine. Our methodology is transferable to applications that treat predictions from classification algorithms as the response variable of interest.</span></p>","language":"English","publisher":"Project Euclid","doi":"10.1214/25-AOAS2096","usgsCitation":"Oram, J., Banner, K.M., Stratton, C., Hoegh, A., and Irvine, K., 2025, Leveraging an observed-data likelihood improves the use of machine learning labels in a Bayesian hierarchical model for bioacoustic data: Annals of Applied Statistics, v. 19, no. 4, p. 2957-2980, https://doi.org/10.1214/25-AOAS2096.","productDescription":"24 p.","startPage":"2957","endPage":"2980","ipdsId":"IP-149507","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":497379,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1214/25-aoas2096","text":"Publisher Index Page"},{"id":497320,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"19","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Oram, Jacob 0009-0001-8405-529X","orcid":"https://orcid.org/0009-0001-8405-529X","contributorId":353522,"corporation":false,"usgs":false,"family":"Oram","given":"Jacob","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":951942,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Banner, Katharine M.","contributorId":363761,"corporation":false,"usgs":false,"family":"Banner","given":"Katharine","middleInitial":"M.","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":951943,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stratton, Christian","contributorId":265905,"corporation":false,"usgs":false,"family":"Stratton","given":"Christian","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":951944,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hoegh, Andrew","contributorId":265906,"corporation":false,"usgs":false,"family":"Hoegh","given":"Andrew","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":951957,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Irvine, Kathryn 0000-0002-6426-940X","orcid":"https://orcid.org/0000-0002-6426-940X","contributorId":220632,"corporation":false,"usgs":true,"family":"Irvine","given":"Kathryn","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":951945,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70272651,"text":"70272651 - 2025 - Depth of magma crystallization and fluid exsolution beneath the porphyry-skarn Cu deposits at Santa Rita and Hanover-Fierro, New Mexico, USA","interactions":[],"lastModifiedDate":"2026-01-05T16:59:46.320524","indexId":"70272651","displayToPublicDate":"2025-11-26T09:23:44","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1472,"text":"Economic Geology","active":true,"publicationSubtype":{"id":10}},"title":"Depth of magma crystallization and fluid exsolution beneath the porphyry-skarn Cu deposits at Santa Rita and Hanover-Fierro, New Mexico, USA","docAbstract":"<p>The depth level at which porphyry Cu–forming magmas fractionated and exsolved mineralizing fluids is actively debated. In the classic model, extensive magma fractionation occurs in large, upper crustal magma chambers, and concomitant fluid exsolution leads to forceful expulsion of residual magmas in the form of porphyry dikes, stocks, and breccia pipes, which subsequently serve as pathways for the mineralizing fluids. In contrast, some recent studies highlighting the role of deep crustal magma fractionation in the production of fertile magmas essentially deny the existence of upper crustal magma chambers at the time of mineralization. To address this, we conducted a detailed thermobarometric investigation of 13 intermediate to felsic, porphyritic intrusive rocks related to porphyry-skarn Cu mineralization at Santa Rita and Hanover-Fierro, New Mexico, United States, representing two premineralization magmas (61–60 Ma), seven synmineralization magmas (60–58 Ma), and four late- to postmineralization magmas (58–57 Ma).</p><p>For each sample, the pressure of last magma crystallization before final magma ascent to the current exposure level was reconstructed based on Al-in-hornblende barometry of small hornblende inclusions trapped within quartz phenocrysts and through titanium-in-quartz (TitaniQ) thermobarometry of the host quartz phenocrysts themselves. Since quartz is one of the last crystallizing magmatic minerals, and no significant phenocryst growth could have occurred in small dikes and stocks after final magma emplacement, quartz phenocrysts and their contained hornblende inclusions record the depth of last magma crystallization before final magma ascent. When present, hornblende phenocrysts and hornblende inclusions within other major phenocrysts were also analyzed. Both quartz and hornblende barometers return consistent average pressures of 3.2 ± 0.4 kbar for the entire suite of pre- to postmineralization magmas, corresponding to depths of 11 to 14&nbsp;km. The synmineralization magmas return even more consistent average pressures of 3.1 ± 0.2 kbar, corresponding to a depth of 12 ± 1&nbsp;km.</p><p>The volume of the mineralizing porphyry dikes and stocks at the emplacement level is far too small to have provided all the fluids and metals required to form the observed ore deposits. Therefore, the majority of the ore-forming fluids must have originated from the magmas that crystallized at 12 ± 1&nbsp;km depth. The ore deposits, conversely, formed at ~5-km paleodepth. This implies that most of the mineralizing fluids traveled an average vertical distance of ~7&nbsp;km from their magmatic source to the eventual site of ore precipitation. The relatively unaltered nature and low veining degree of deeper parts of mineralized porphyry dikes and stocks suggest that the fluid transport through these intrusive bodies occurred mostly at near-solidus conditions by means of fluid percolation along grain boundaries.</p><p>In summary, our results suggest that (1) a large, upper crustal pluton exists ~7 km beneath the Santa Rita and Hanover-Fierro deposits; (2) abundant phenocryst crystallization occurred at this depth level; and (3) this pluton was the main source for the exsolution of ore-forming fluids. However, the investigated rocks have elevated whole-rock Sr/Y ratios, indicating magma fractionation at deep crustal levels. As a result, our preferred model is a combination of the two end-member models introduced above, with most magma fractionation having occurred in the deep crust and with residual, intermediate to felsic melts having ascended and accumulated at 11 to 14 km paleodepth, where they continued to crystallize with comparatively little crystal-liquid separation, before some of these magmas ascended further to shallow levels and quenched to porphyries.</p>","language":"English","publisher":"Society of Economic Geology","doi":"10.5382/econgeo.5197","usgsCitation":"Audétat, A., Chang, J., and Gaynor, S.P., 2025, Depth of magma crystallization and fluid exsolution beneath the porphyry-skarn Cu deposits at Santa Rita and Hanover-Fierro, New Mexico, USA: Economic Geology, v. 120, no. 7, p. 1679-1699, https://doi.org/10.5382/econgeo.5197.","productDescription":"21 p.","startPage":"1679","endPage":"1699","ipdsId":"IP-174016","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":496982,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Mexico","otherGeospatial":"Hanover-Fierro deposit, Santa Rita mine","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -108,\n              32.875\n            ],\n            [\n              -108.1667,\n              32.875\n            ],\n            [\n              -108.1667,\n              32.75\n            ],\n            [\n              -108,\n              32.75\n            ],\n            [\n              -108,\n              32.875\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"120","issue":"7","noUsgsAuthors":false,"publicationDate":"2025-11-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Audétat, Andreas","contributorId":363151,"corporation":false,"usgs":false,"family":"Audétat","given":"Andreas","affiliations":[{"id":83309,"text":"Bavarian Geoinstitute, University of Bayreuth","active":true,"usgs":false}],"preferred":false,"id":951173,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chang, Jia","contributorId":363152,"corporation":false,"usgs":false,"family":"Chang","given":"Jia","affiliations":[{"id":83309,"text":"Bavarian Geoinstitute, University of Bayreuth","active":true,"usgs":false}],"preferred":false,"id":951174,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gaynor, Sean Patrick 0000-0002-8353-511X","orcid":"https://orcid.org/0000-0002-8353-511X","contributorId":346264,"corporation":false,"usgs":true,"family":"Gaynor","given":"Sean","email":"","middleInitial":"Patrick","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":951175,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70273755,"text":"70273755 - 2025 - Twenty years (2000-2020) of butterfly monitoring data across the contiguous United States","interactions":[],"lastModifiedDate":"2026-01-28T16:44:37.745111","indexId":"70273755","displayToPublicDate":"2025-11-22T09:37:47","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3907,"text":"Scientific Data","active":true,"publicationSubtype":{"id":10}},"title":"Twenty years (2000-2020) of butterfly monitoring data across the contiguous United States","docAbstract":"<p><span id=\"_mce_caret\" data-mce-bogus=\"1\" data-mce-type=\"format-caret\"><span>We present the most comprehensive, integrated, butterfly monitoring dataset ever assembled for the United States. It contains over 1.2 million count records, from 65,000 surveys, representing over 12.6 million individual butterflies. To compile this dataset, we integrated data and harmonized taxonomy across 19 butterfly monitoring programs in the United States – one national, 13 statewide, and 5 local (e.g. individual county or National Park) in scale. In addition to the data, we also provide the taxonomic dictionary used to crosswalk butterfly taxonomy across programs, and the code used to assemble the integrated dataset. The publication of this dataset will inspire new analyses of butterfly population trends and drivers that help to identify solutions to the biodiversity crisis.</span></span></p>","language":"English","publisher":"Springer Nature","doi":"10.1038/s41597-025-05513-8","usgsCitation":"Henry, E.H., Edwards, C., Shirey, V., Pippen, J.S., Waetjen, D., Forister, M.L., Larsen, E., Schultz, C.B., Michielini, J., Brockman, N., Burls, K., Drum, R., Gatch, M., Glassberg, J., Hamlett, N., Hershcovich, S.V., Le, C., McGaffin, S., Meilinger, J., Richter, L., Rochefort, R., Schelz, C., Shapiro, A.M., Sullivan, K., Taron, D., Thogmartin, W.E., Walker, A., Westphal, A., Wiedmann, J., Wilcockson, I.U., Zaspel, J., and Ries, L., 2025, Twenty years (2000-2020) of butterfly monitoring data across the contiguous United States: Scientific Data, v. 12, 1869, 8 p., https://doi.org/10.1038/s41597-025-05513-8.","productDescription":"1869, 8 p.","ipdsId":"IP-174696","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":499339,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41597-025-05513-8","text":"Publisher Index Page"},{"id":499180,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"contiguous United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"geometry\": {\n        \"type\": \"MultiPolygon\",\n        \"coordinates\": [\n          [\n            [\n              [\n                -94.81758,\n                49.38905\n              ],\n              [\n                -94.64,\n                48.84\n              ],\n              [\n                -94.32914,\n                48.67074\n              ],\n              [\n                -93.63087,\n                48.60926\n              ],\n       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,{"id":70272622,"text":"70272622 - 2025 - Drowned river mouth lakes are winter foraging habitats for the expanding Lake Michigan cisco Coregonus artedi population","interactions":[],"lastModifiedDate":"2025-11-26T14:08:32.471574","indexId":"70272622","displayToPublicDate":"2025-11-22T08:02:37","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Drowned river mouth lakes are winter foraging habitats for the expanding Lake Michigan cisco <i>Coregonus artedi</i> population","title":"Drowned river mouth lakes are winter foraging habitats for the expanding Lake Michigan cisco Coregonus artedi population","docAbstract":"<p><span>Characterizing fish movements is required for understanding habitat use, energy flow, and trophic structure and can inform fisheries management. Drowned river mouth (DRM) lakes are productive inland habitats in the Laurentian Great Lakes basin used by migratory fishes. Despite recognition of their ecological connections to the Great Lakes, the value of DRM lakes as seasonal habitats is not well understood for many fishes. One such species, cisco&nbsp;</span><i>Coregonus artedi</i><span>, has recently expanded in Lake Michigan from near extirpation to higher relative abundances in the northeastern portion of the lake. Cisco are recreationally harvested in some DRM lakes during winter, but little is known about cisco movement patterns and ecology. In winter 2022 and 2023, we collected cisco from three DRM lakes along the eastern shores of Lake Michigan (Lake Charlevoix, Portage Lake, Muskegon Lake) to characterize genetics, morphometrics, and diets. We also implanted telemetry tags in 20 cisco collected in Lake Charlevoix to examine movement patterns and determine DRM lake residency (i.e., seasonal vs. year-round). We found no consistent genetic or morphometric differentiation across DRM lakes, suggesting that recolonization began from a single stock. Fish were the only diet item found in cisco guts collected during winter months. Movement patterns from Lake Charlevoix indicated strong spawning site fidelity to Grand Traverse Bay as well as non-spawning site fidelity. However, given the presence of cisco in southern DRM lakes and some site-specific differences in morphometrics, managers could benefit from further research to determine whether spawning occurs in southern Lake Michigan.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jglr.2025.102683","usgsCitation":"Tingley, R.W., Hondorp, D.W., Turschak, B.A., Pothoven, S.A., Ackiss, A.S., Jonas, J., Fetzer, W.W., Leonhardt, B.S., Honsey, A.E., Elliott, J., Egedy, L., Brant, C., Benes, L., Kozlauskos, K., Renauer-Bova, R., and Ropp, A.J., 2025, Drowned river mouth lakes are winter foraging habitats for the expanding Lake Michigan cisco Coregonus artedi population: Journal of Great Lakes Research, https://doi.org/10.1016/j.jglr.2025.102683.","ipdsId":"IP-179185","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":496896,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"edition":"Online First","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Tingley, Ralph W. 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,{"id":70272228,"text":"70272228 - 2025 - Observational, virological, and serological data provide insights into an outbreak of highly pathogenic avian influenza among wild birds on the Yukon-Kuskokwim Delta, Alaska in 2022","interactions":[],"lastModifiedDate":"2025-11-19T16:38:10.441626","indexId":"70272228","displayToPublicDate":"2025-11-18T08:55:18","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2507,"text":"Journal of Wildlife Diseases","active":true,"publicationSubtype":{"id":10}},"title":"Observational, virological, and serological data provide insights into an outbreak of highly pathogenic avian influenza among wild birds on the Yukon-Kuskokwim Delta, Alaska in 2022","docAbstract":"<p><span>In 2021–22, clade 2.3.4.4b highly pathogenic avian influenza (HPAI) viruses were introduced by wild birds into North America, leading to geographically widespread disease. In response to HPAI outbreaks throughout late 2021 and early 2022, we recorded observations of sick and dead birds, estimated abundance of carcasses, collected swab and sera samples to detect viruses, and monitored bird nesting on the Yukon-Kuskokwim Delta region of Alaska to document potential effects of disease. Thirty-six reports of sick and dead birds were registered across the region. Nineteen carcasses were opportunistically collected for diagnostic testing, of which 12 were confirmed to be infected with clade 2.3.4.4b HPAI viruses. Carcass abundance estimates from line-distance sampling provided evidence that the most common species of dead birds from the western Yukon-Kuskokwim Delta region were Cackling Goose (</span><i>Branta hutchinsii minima</i><span>), Glaucous Gull (</span><i>Larus hyperboreus</i><span>), and Black Brant (</span><i>Branta bernicla nigricans</i><span>). Only one paired cloacal and oropharyngeal swab sample from a Northern Pintail (</span><i>Anas acuta</i><span>) tested positive for clade 2.3.4.4b HPAI virus, out of 464 live-captured duck and goose samples. Of 195 sera samples from waterfowl screened for antibodies reactive to influenza A viruses, antibodies were found in 41–98% of samples collected from Emperor Goose (</span><i>Anser canagicus</i><span>), Cackling Goose, Black Brant, and Spectacled Eider (</span><i>Somateria fischeri</i><span>). In addition, 15–98% of the same sera samples were reactive to a clade 2.3.4.4b H5 antigen. Fewer Black Brant and Emperor Goose nests were found on long-term study plots during 2022 than in previous years. Collectively, we found that HPAI viruses affected at least seven species of wild birds inhabiting the region during 2022. The full scope of impacts of HPAI at this location during 2022 is unknown, but our data indicate that acute effects to avian population health on the Yukon-Kuskokwim Delta region were likely modest.</span></p>","language":"English","publisher":"Wildlife Disease Association","doi":"10.7589/JWD-D-24-00199","usgsCitation":"Daniels, B., Osnas, E.E., Boldenow, M., Gerlach, R., Ahlstrom, C., Coburn, S., Brook, M.J., Brubaker, M., Fischer, J., Koons, D.N., Matz, A., Murphy, M., Rizzolo, D., Scott, L.C., Sinnett, D.R., Thompson, J.M., Lenoch, J., Kim Torchetti, M., Stallknecht, D., Poulson, R., and Ramey, A.M., 2025, Observational, virological, and serological data provide insights into an outbreak of highly pathogenic avian influenza among wild birds on the Yukon-Kuskokwim Delta, Alaska in 2022: Journal of Wildlife Diseases, v. 61, no. 4, p. 1010-1027, https://doi.org/10.7589/JWD-D-24-00199.","productDescription":"18 p.","startPage":"1010","endPage":"1027","ipdsId":"IP-171898","costCenters":[{"id":65299,"text":"Alaska Science Center Ecosystems","active":true,"usgs":true}],"links":[{"id":496752,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.7589/jwd-d-24-00199","text":"Publisher Index Page"},{"id":496647,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Yukon-Kuskokwim Delta","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -166.4746289834893,\n              63.36414571785119\n            ],\n            [\n              -166.4746289834893,\n              59.79632510918222\n            ],\n            [\n              -157.1960098482071,\n              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Georgia, Athens, GA 30602, USA.","active":true,"usgs":false}],"preferred":false,"id":950517,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Ramey, Andrew M. 0000-0002-3601-8400 aramey@usgs.gov","orcid":"https://orcid.org/0000-0002-3601-8400","contributorId":1872,"corporation":false,"usgs":true,"family":"Ramey","given":"Andrew","email":"aramey@usgs.gov","middleInitial":"M.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":950518,"contributorType":{"id":1,"text":"Authors"},"rank":21}]}}
,{"id":70272215,"text":"70272215 - 2025 - Cryptic life history diversity supports endangered species recovery in an ultra-urbanized landscape","interactions":[],"lastModifiedDate":"2025-11-19T15:31:57.22913","indexId":"70272215","displayToPublicDate":"2025-11-18T08:28:18","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3358,"text":"Scientific Reports","active":true,"publicationSubtype":{"id":10}},"title":"Cryptic life history diversity supports endangered species recovery in an ultra-urbanized landscape","docAbstract":"<p><span>Urban landscapes are often overlooked in conservation planning, allowing human activities to take precedence in ecosystem management. However, even heavily modified environments can support diverse species profiles, but continued expansion of the human footprint could transform these biodiversity hotspots into ecological traps that serve as hidden catalysts for demographic declines. In the backdrop of one of the world’s most urbanized landscapes-New York City, USA—is a federally endangered population of shortnose sturgeon (</span><i>Acipenser brevirostrum</i><span>) that has been quietly recovering for several decades despite many demographic threats. Here, we identify a unique behavioral phenotype of shortnose sturgeon that occupies habitats in New York Harbor in late spring and fall, likely using the area to optimize bioenergetic processes. As this study highlights, urbanized environments can be a nexus for cryptic phenotypic diversity which, if overlooked, can disrupt eco-evolutionary processes and contribute to population and species loss.</span></p>","language":"English","publisher":"Springer Nature","doi":"10.1038/s41598-025-24360-6","usgsCitation":"White, S.L., Higgs, A., and Fox, D., 2025, Cryptic life history diversity supports endangered species recovery in an ultra-urbanized landscape: Scientific Reports, v. 15, 40634, 8 p., https://doi.org/10.1038/s41598-025-24360-6.","productDescription":"40634, 8 p.","ipdsId":"IP-178198","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":496744,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-025-24360-6","text":"Publisher Index Page"},{"id":496636,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","city":"New York City","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -74.09993061657431,\n              40.736082719013496\n            ],\n            [\n              -74.09993061657431,\n              40.588831128093005\n            ],\n            [\n              -73.96403648299037,\n              40.588831128093005\n            ],\n            [\n              -73.96403648299037,\n              40.736082719013496\n            ],\n            [\n              -74.09993061657431,\n              40.736082719013496\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"15","noUsgsAuthors":false,"publicationDate":"2025-11-18","publicationStatus":"PW","contributors":{"authors":[{"text":"White, Shannon L. 0000-0003-4687-6596","orcid":"https://orcid.org/0000-0003-4687-6596","contributorId":263424,"corporation":false,"usgs":true,"family":"White","given":"Shannon","email":"","middleInitial":"L.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":950464,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Higgs, Amanda","contributorId":225402,"corporation":false,"usgs":false,"family":"Higgs","given":"Amanda","affiliations":[{"id":13678,"text":"New York State Department of Environmental Conservation","active":true,"usgs":false}],"preferred":false,"id":950465,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fox, Dewayne","contributorId":340954,"corporation":false,"usgs":false,"family":"Fox","given":"Dewayne","affiliations":[{"id":37219,"text":"Delaware State University","active":true,"usgs":false}],"preferred":false,"id":950466,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70272577,"text":"70272577 - 2025 - Performance analysis of oil recovery and CO2 retention in a greenfield residual oil zone: CO2-EOR in Tall Cotton Field (Permian Basin, West Texas, USA)","interactions":[],"lastModifiedDate":"2025-11-24T16:11:13.736607","indexId":"70272577","displayToPublicDate":"2025-11-15T09:01:56","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":22979,"text":"Carbon Capture Science and Technology","active":true,"publicationSubtype":{"id":10}},"title":"Performance analysis of oil recovery and CO2 retention in a greenfield residual oil zone: CO2-EOR in Tall Cotton Field (Permian Basin, West Texas, USA)","docAbstract":"<p><span>Residual oil zones (ROZs) can offer significant oil resources via enhanced oil recovery (EOR) as well as subsurface carbon dioxide (CO</span><sub>2</sub><span>) retention during injection. If injected CO</span><sub>2</sub><span>&nbsp;is anthropogenic, the ROZs can offer a substantial geologic storage potential. The ROZs below the oil/water contact (OWC) of main pay zones (MPZ) in conventional reservoirs or brownfields, are more commonly developed for CO</span><sub>2</sub><span>&nbsp;injection and oil production and reported in the literature. However, CO</span><sub>2</sub><span>-EOR in greenfield ROZs, reservoirs without a MPZ present, have rarely been developed for CO</span><sub>2</sub><span>-EOR operation. The Tall Cotton Field of West Texas, Permian Basin, which started production in 2015 (Phase 1) and expanded in 2017 (Phase 2) from the San Andres Limestone, is one of the first examples of greenfield ROZs developed for EOR by injecting CO</span><sub>2</sub><span>.</span></p><p><span>This paper analyses EOR and CO</span><sub>2</sub><span>&nbsp;retention performance of Tall Cotton Field using allocated injection and production data from inverted 5-spot well patterns of Phase-1 and -2 developments. Production and injection data allocated to each of the 28 identified patterns (nine 20-acre patterns for Phase-1, three 20-acre and sixteen 10-acre patterns for Phase-2) were analyzed for historical and forecasted oil recovery using ratio-trend decline analysis, and for CO</span><sub>2</sub><span>&nbsp;retention performance of the patterns. The allocated data were further used to calculate injected reservoir pore volume and void replacement ratios (VRR) for the analysis period. Quantitative results indicated that oil recovery factors of the 5-spot patterns varied between 4–10 %, and 5–30 % between the end of injection and the forecast periods, respectively. Storage of CO</span><sub>2</sub><span>, on the other hand, increased to a mean value of ∼7130 MMscf per pattern in Phase-1 and to a mean storage of 3700 MMscf per pattern in Phase-2 until the end of injection, followed by a decline after the end of injection and into the forecast period. Resulting CO</span><sub>2</sub><span>&nbsp;utilization factors ∼6–50 Mscf/bbl were estimated at the end of injection. Overall, presented results suggested that developing greenfield ROZs for CO</span><sub>2</sub><span>-EOR can be as promising as brownfield ROZs and mature MPZs for EOR and underground storage of injected CO</span><sub>2</sub><span>. For Tall Cotton Field, results suggest that Phase-2 patterns generally outperformed Phase-1 for oil recovery factors, while Phase-1 performed better in CO</span><sub>2</sub><span>&nbsp;retention performance metrics. This is the first study in the literature that reports a detailed CO</span><sub>2</sub><span>-EOR performance analysis of a greenfield ROZ in the Permian Basin, which can potentially allow for comparison with MPZs and brownfield ROZs.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.ccst.2025.100544","usgsCitation":"Karacan, C.O., 2025, Performance analysis of oil recovery and CO2 retention in a greenfield residual oil zone: CO2-EOR in Tall Cotton Field (Permian Basin, West Texas, USA): Carbon Capture Science and Technology, v. 17, 100544, 14 p., https://doi.org/10.1016/j.ccst.2025.100544.","productDescription":"100544, 14 p.","ipdsId":"IP-179246","costCenters":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":496930,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ccst.2025.100544","text":"Publisher Index Page"},{"id":496830,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Texas","county":"Gaines County","otherGeospatial":"Tall Cotton Field","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -103.04678856680947,\n              33.3881629621319\n            ],\n            [\n              -103.04678856680947,\n              31.601101499990648\n            ],\n            [\n              -101.42024271710294,\n              31.601101499990648\n            ],\n            [\n              -101.42024271710294,\n              33.3881629621319\n            ],\n            [\n              -103.04678856680947,\n              33.3881629621319\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"17","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Karacan, C. Ozgen 0000-0002-0947-8241","orcid":"https://orcid.org/0000-0002-0947-8241","contributorId":201991,"corporation":false,"usgs":true,"family":"Karacan","given":"C.","email":"","middleInitial":"Ozgen","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":950843,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70272686,"text":"70272686 - 2025 - Occurrence and surface availability of Siskiyou Mountains Salamanders (Plethodon stormi) and Scott Bar Salamanders (P. asupak) in northern California","interactions":[],"lastModifiedDate":"2026-01-07T17:34:57.208708","indexId":"70272686","displayToPublicDate":"2025-11-06T09:41:50","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1892,"text":"Herpetologica","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Occurrence and surface availability of Siskiyou Mountains Salamanders (<i>Plethodon stormi</i>) and Scott Bar Salamanders (<i>P. asupak</i>) in northern California","title":"Occurrence and surface availability of Siskiyou Mountains Salamanders (Plethodon stormi) and Scott Bar Salamanders (P. asupak) in northern California","docAbstract":"<p><span>Estimating the distributions of cryptic species is essential for conservation, yet our understanding is hampered by animal behavior and imperfect detection. We developed and implemented a multiscale occupancy survey protocol to estimate the probability of occurrence, probability of being active on the surface, and detection probability of two range-restricted terrestrial salamanders, Scott Bar Salamanders (</span><i>Plethodon asupak</i><span>) and Siskiyou Mountains Salamanders (</span><i>P. stormi</i><span>), in interior northern California, USA. We established survey sites near locations of historical occurrence of these salamanders and surveyed each site on one to six visits in late fall 2023 and spring 2024. We compared models with different environmental variables for predicting salamander occurrence and surface activity. Much model selection uncertainty in the effects of covariates existed, but the model with most support indicated that&nbsp;</span><i>Plethodon</i><span>&nbsp;salamanders in interior northern California were more likely to occur at sites near recent historical occurrences that had longer growing seasons after controlling for elevation and aspect.&nbsp;</span><i>Plethodon stormi</i><span>&nbsp;or&nbsp;</span><i>P. asupak</i><span>&nbsp;surface activity was higher at night than during the day and was highest when substrates were cool and moist. Our survey protocol was successful for quantifying the effects of site and visit characteristics on&nbsp;</span><i>P. stormi</i><span>&nbsp;or&nbsp;</span><i>P. asupak</i><span>&nbsp;occurrence and availability; minor modifications will likely improve its utility for providing unbiased inference about salamander occurrence and surface activity.</span></p>","language":"English","publisher":"Allen Press","doi":"10.1655/Herpetologica-D-25-00011","usgsCitation":"Halstead, B., Macias, D., Moss, C., Kleeman, P.M., and Rose, J.P., 2025, Occurrence and surface availability of Siskiyou Mountains Salamanders (Plethodon stormi) and Scott Bar Salamanders (P. asupak) in northern California: Herpetologica, v. 81, no. 4, p. 336-345, https://doi.org/10.1655/Herpetologica-D-25-00011.","productDescription":"10 p.","startPage":"336","endPage":"345","ipdsId":"IP-178431","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":497695,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1655/herpetologica-d-25-00011","text":"Publisher Index Page"},{"id":497055,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","county":"Siskiyou County","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -123.5,\n              41.9167\n            ],\n            [\n              -123.5,\n              41.5833\n            ],\n            [\n              -122.75,\n              41.5833\n            ],\n            [\n              -122.75,\n              41.9167\n            ],\n            [\n              -123.5,\n              41.9167\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"81","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Halstead, Brian J. 0000-0002-5535-6528 bhalstead@usgs.gov","orcid":"https://orcid.org/0000-0002-5535-6528","contributorId":215986,"corporation":false,"usgs":true,"family":"Halstead","given":"Brian","email":"bhalstead@usgs.gov","middleInitial":"J.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":951331,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Macias, Daniel Antonio 0000-0002-4891-3656","orcid":"https://orcid.org/0000-0002-4891-3656","contributorId":349883,"corporation":false,"usgs":true,"family":"Macias","given":"Daniel Antonio","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":951332,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Moss, Casey D.","contributorId":359464,"corporation":false,"usgs":false,"family":"Moss","given":"Casey D.","affiliations":[],"preferred":false,"id":951333,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kleeman, Patrick M. 0000-0001-6567-3239 pkleeman@usgs.gov","orcid":"https://orcid.org/0000-0001-6567-3239","contributorId":3948,"corporation":false,"usgs":true,"family":"Kleeman","given":"Patrick","email":"pkleeman@usgs.gov","middleInitial":"M.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":951334,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rose, Jonathan P. 0000-0003-0874-9166 jprose@usgs.gov","orcid":"https://orcid.org/0000-0003-0874-9166","contributorId":199339,"corporation":false,"usgs":true,"family":"Rose","given":"Jonathan","email":"jprose@usgs.gov","middleInitial":"P.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":951335,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70272218,"text":"70272218 - 2025 - Spatial distribution and relative biomass of bigheaded carps in Lake Balaton, Hungary estimated from an environmental DNA survey","interactions":[],"lastModifiedDate":"2025-11-19T15:47:46.625525","indexId":"70272218","displayToPublicDate":"2025-11-06T09:37:26","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Spatial distribution and relative biomass of bigheaded carps in Lake Balaton, Hungary estimated from an environmental DNA survey","docAbstract":"<p><span>Silver carp (</span><i>Hypophthalmichthys nobilis</i><span>), bighead carp (</span><i>H. molitrix</i><span>) and their hybrids, collectively known as bigheaded carps, have been introduced to Lake Balaton, Hungary. The current stock sizes are difficult to assess. We investigated environmental DNA (eDNA) techniques targeted for bigheaded carps, assessed the spatial distribution of eDNA in Lake Balaton, compared eDNA concentrations to environmental variables to assess potential habitat selection based on those variables, and provided an estimate of biomass of bigheaded carps relative to eDNA shedding rates per unit biomass observed in controlled experiments. Water samples were collected from 70 sites in an array across the lake. Biomass estimation was calculated using mean eDNA concentration obtained by quantitative PCR of the samples and previously determined eDNA shedding rates of bigheaded carps under controlled conditions in a laboratory. Concentration of eDNA was highly variable between sites, resulting in wide confidence intervals. Basins did not significantly differ in eDNA concentration, and there were no strong relationships between environmental variables and eDNA concentration, indications that bigheaded carps use the entire lake. The model provided an estimate of 4,830 metric tonnes (2,750–8,030 tonnes) of bigheaded carps in Lake Balaton, or 81.0 kg/ha. The eDNA method produced a value close to previous estimates by traditional means of total biomass of bigheaded carps in the lake, and like traditional methods, there was a broad confidence interval on the estimate of the mean. The results of the present study support the utility of aquatic eDNA analysis, and the need for further comparisons with fisheries methods and supporting data from laboratory studies.</span></p>","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0335950","usgsCitation":"Boross, N., Laszlo, A., Chapman, D.C., Boros, G., Vitál, Z., Tóth, V., Thompson, N., Klymus, K.E., and Richter, C.A., 2025, Spatial distribution and relative biomass of bigheaded carps in Lake Balaton, Hungary estimated from an environmental DNA survey: PLoS ONE, v. 20, no. 11, 0335950, 15 p., https://doi.org/10.1371/journal.pone.0335950.","productDescription":"0335950, 15 p.","ipdsId":"IP-178103","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":496746,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0335950","text":"Publisher Index Page"},{"id":496639,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Hungary","otherGeospatial":"Lake Balaton","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              18.21350370081612,\n              47.10491295878799\n            ],\n            [\n              17.172489215123477,\n              47.10491295878799\n            ],\n            [\n              17.172489215123477,\n              46.62325119241811\n            ],\n            [\n              18.21350370081612,\n              46.62325119241811\n            ],\n            [\n              18.21350370081612,\n              47.10491295878799\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  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Research Center","active":true,"usgs":false}],"preferred":false,"id":950469,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Boros, Gergely","contributorId":295274,"corporation":false,"usgs":false,"family":"Boros","given":"Gergely","email":"","affiliations":[{"id":63813,"text":"Centre for Ecological Research, Balaton Limnological Institute","active":true,"usgs":false}],"preferred":false,"id":950470,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Vitál, Zoltán","contributorId":352562,"corporation":false,"usgs":false,"family":"Vitál","given":"Zoltán","affiliations":[{"id":84260,"text":"Hungarian University of Agriculture and Life Sciences","active":true,"usgs":false}],"preferred":false,"id":950471,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Tóth, Viktor","contributorId":362437,"corporation":false,"usgs":false,"family":"Tóth","given":"Viktor","affiliations":[{"id":86526,"text":"HUN-REN Balaton Limnological Research Institute, Hungary","active":true,"usgs":false}],"preferred":false,"id":950472,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Thompson, Nathan 0000-0002-1372-6340 nthompson@usgs.gov","orcid":"https://orcid.org/0000-0002-1372-6340","contributorId":196133,"corporation":false,"usgs":true,"family":"Thompson","given":"Nathan","email":"nthompson@usgs.gov","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":950473,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Klymus, Katy E. 0000-0002-8843-6241 kklymus@usgs.gov","orcid":"https://orcid.org/0000-0002-8843-6241","contributorId":5043,"corporation":false,"usgs":true,"family":"Klymus","given":"Katy","email":"kklymus@usgs.gov","middleInitial":"E.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":950474,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Richter, Catherine A. 0000-0001-7322-4206 crichter@usgs.gov","orcid":"https://orcid.org/0000-0001-7322-4206","contributorId":138994,"corporation":false,"usgs":true,"family":"Richter","given":"Catherine","email":"crichter@usgs.gov","middleInitial":"A.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":950475,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70273494,"text":"70273494 - 2025 - Development of genomic markers for monitoring and research on plethodontid salamanders","interactions":[],"lastModifiedDate":"2026-01-20T16:29:44.920088","indexId":"70273494","displayToPublicDate":"2025-11-06T09:21:20","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Development of genomic markers for monitoring and research on plethodontid salamanders","docAbstract":"<p><span id=\"_mce_caret\" data-mce-bogus=\"1\" data-mce-type=\"format-caret\"><span>Despite the importance of plethodontid salamanders and their vulnerability to ongoing environmental change, they are inherently difficult to monitor due to their cryptic nature. Recent advances in genomics have created new opportunities for monitoring of populations and their responses to environmental perturbations. In this study, we developed a new target capture-based genomic panel for the purposes of genetic monitoring in plethodontid salamanders. We demonstrate its utility in several distantly related species and present an example application in two representative species with co-occurring distributions but different ecological attributes and expected patterns of population structure:&nbsp;</span><i>Plethodon jordani</i><span>&nbsp;and&nbsp;</span><i>Desmognathus wrighti</i><span>. Although the number of successfully assembled loci declined with phylogenetic distance from the original reference species (</span><i>Desmognathus</i><span>&nbsp;spp), we obtained high-quality data from thousands of loci from species in all four genera tested (</span><i>Desmognathus</i><span>,&nbsp;</span><i>Plethodon</i><span>,&nbsp;</span><i>Eurycea</i><span>, and&nbsp;</span><i>Gyrinophilus</i><span>), which span the deepest split in Plethodontidae. Landscape genetic analyses detected weak but statistically significant geographic structure in&nbsp;</span><i>P. jordani</i><span>, and much stronger geographic structure in&nbsp;</span><i>D. wrighti</i><span>, as expected based on the lower population density and likely lower dispersal ability of&nbsp;</span><i>D. wrighti</i><span>. Our target capture panel is broadly applicable across salamanders in Plethodontidae and has the potential to provide data for a wide range of phylogenetic, biogeographic, and population genetics research questions.</span></span></p>","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0336236","usgsCitation":"Fitzpatrick, B.M., Jones, K., Aunins, A.W., Eackles, M.S., and Kazyak, D.C., 2025, Development of genomic markers for monitoring and research on plethodontid salamanders: PLoS ONE, v. 20, no. 11, e0336236, 17 p., https://doi.org/10.1371/journal.pone.0336236.","productDescription":"e0336236, 17 p.","ipdsId":"IP-179317","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":498922,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0336236","text":"Publisher Index Page"},{"id":498782,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Carolina, Tennessee","otherGeospatial":"Great Smoky Mountains National Park","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -83.96979895915521,\n              35.68689851036355\n            ],\n            [\n              -84.05501149014529,\n              35.55141202602384\n            ],\n            [\n              -83.96678886713649,\n              35.43799305033697\n            ],\n            [\n              -83.55568366891563,\n              35.42976785901836\n            ],\n            [\n              -83.09885998619994,\n              35.48881199038594\n            ],\n            [\n              -83.01407939098402,\n              35.69152675352798\n            ],\n            [\n              -83.17690302454709,\n              35.814788263627534\n            ],\n            [\n              -83.96979895915521,\n              35.68689851036355\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"20","issue":"11","noUsgsAuthors":false,"publicationDate":"2025-11-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Fitzpatrick, Benjamin M.","contributorId":336140,"corporation":false,"usgs":false,"family":"Fitzpatrick","given":"Benjamin","email":"","middleInitial":"M.","affiliations":[{"id":80760,"text":"1. Department of Ecology and Evolutionary Biology, University of Tennessee, Knoxville, Tennessee","active":true,"usgs":false}],"preferred":false,"id":953978,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jones, Kara Suzanne 0000-0002-8168-0815","orcid":"https://orcid.org/0000-0002-8168-0815","contributorId":331477,"corporation":false,"usgs":true,"family":"Jones","given":"Kara Suzanne","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":953979,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Aunins, Aaron W. 0000-0001-5240-1453 aaunins@usgs.gov","orcid":"https://orcid.org/0000-0001-5240-1453","contributorId":5863,"corporation":false,"usgs":true,"family":"Aunins","given":"Aaron","email":"aaunins@usgs.gov","middleInitial":"W.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":953980,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Eackles, Michael S. 0000-0001-5624-5769 meackles@usgs.gov","orcid":"https://orcid.org/0000-0001-5624-5769","contributorId":218936,"corporation":false,"usgs":true,"family":"Eackles","given":"Michael","email":"meackles@usgs.gov","middleInitial":"S.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":953981,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kazyak, David C. 0000-0001-9860-4045","orcid":"https://orcid.org/0000-0001-9860-4045","contributorId":140409,"corporation":false,"usgs":true,"family":"Kazyak","given":"David","email":"","middleInitial":"C.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":953982,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70272097,"text":"70272097 - 2025 - Global recreational consumption of non-native inland fish: Higher economic benefits, but lower nutritional value and climate resilience","interactions":[],"lastModifiedDate":"2025-11-14T14:52:00.136041","indexId":"70272097","displayToPublicDate":"2025-11-06T07:48:01","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Global recreational consumption of non-native inland fish: Higher economic benefits, but lower nutritional value and climate resilience","docAbstract":"<p><span>Inland recreational fisheries are globally significant leisure pursuits, with well-documented benefits to human health and well-being, but also one of the principal drivers of non-native fish introductions to enhance fishing opportunities, whether for sport or sustenance. In this study, we assess the relative reliance of global inland recreational fisheries on non-native versus native species for harvest. We further examine how this reliance varies by economic and nutritional value as well as the climate vulnerability of the species involved. We demonstrate that, of the 1,325,851&nbsp;t of inland recreational fishes recreationally harvested for consumption worldwide in 2021, non-native fish were a small proportion (4&nbsp;%; 53,651&nbsp;t). On a global scale, non-native fish contributed a net positive 38.2&nbsp;% economic value to inland recreational harvest. However, they also contributed a net negative −21.9&nbsp;% nutritional value to inland recreational harvest. Non-native fishes were also more climate vulnerable (i.e., higher average climate vulnerability index values) and thus proportionally increased overall estimates of climate vulnerability with a net positive of 70.9&nbsp;%. Our results quantitatively demonstrate that non-native species play a more important role in inland consumptive recreational fisheries than their mere harvest volume would suggest. However, many nuances were seen on the continent and country scale, which reflect the complexity of fisher behavior, fish distribution and socio-economic factors. Our findings help unravel the complex effects of non-native species on human activities and underscore the need to evaluate their global impacts holistically.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2025.180872","usgsCitation":"Milardi, M., Wood, L.E., Nyboer, E.A., Embke, H., Phang, S.C., and Lynch, A.J., 2025, Global recreational consumption of non-native inland fish: Higher economic benefits, but lower nutritional value and climate resilience: Science of the Total Environment, v. 1005, 180872, 9 p., https://doi.org/10.1016/j.scitotenv.2025.180872.","productDescription":"180872, 9 p.","ipdsId":"IP-179171","costCenters":[{"id":36940,"text":"National Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":500621,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://hdl.handle.net/10919/141326","text":"External Repository"},{"id":496474,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"1005","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Milardi, Marco","contributorId":201384,"corporation":false,"usgs":false,"family":"Milardi","given":"Marco","email":"","affiliations":[],"preferred":false,"id":950049,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wood, Louisa E.","contributorId":292289,"corporation":false,"usgs":false,"family":"Wood","given":"Louisa","middleInitial":"E.","affiliations":[],"preferred":false,"id":950050,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nyboer, Elizabeth A.","contributorId":360818,"corporation":false,"usgs":false,"family":"Nyboer","given":"Elizabeth","middleInitial":"A.","affiliations":[],"preferred":false,"id":950051,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Embke, Holly Susan 0000-0002-9897-7068","orcid":"https://orcid.org/0000-0002-9897-7068","contributorId":358337,"corporation":false,"usgs":true,"family":"Embke","given":"Holly Susan","affiliations":[{"id":65882,"text":"Midwest Climate Adaptation Science Center","active":true,"usgs":true}],"preferred":true,"id":950052,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Phang, Sui C.","contributorId":360819,"corporation":false,"usgs":false,"family":"Phang","given":"Sui","middleInitial":"C.","affiliations":[],"preferred":false,"id":950053,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lynch, Abigail J. 0000-0001-8449-8392","orcid":"https://orcid.org/0000-0001-8449-8392","contributorId":204271,"corporation":false,"usgs":true,"family":"Lynch","given":"Abigail","middleInitial":"J.","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":950054,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70273274,"text":"70273274 - 2025 - Landsat-derived rainfed and irrigated-area product for conterminous United States for the year 2020 (LRIP30 CONUS 2020) using supervised and unsupervised machine learning on the cloud","interactions":[],"lastModifiedDate":"2025-12-29T16:30:45.746731","indexId":"70273274","displayToPublicDate":"2025-11-01T10:22:57","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5987,"text":"Photogrammetric Engineering & Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Landsat-derived rainfed and irrigated-area product for conterminous United States for the year 2020 (LRIP30 CONUS 2020) using supervised and unsupervised machine learning on the cloud","docAbstract":"<p><span>Accurate maps of irrigated and rainfed croplands are crucial for assessing global food and water security. Irrigated croplands yield two to four times more grain and biomass than rainfed croplands. To meet rising food demand, the proportion of cropland that is irrigated must be increased globally. Because agriculture uses 80% to 90% of global fresh water, understanding changes in cropland extent, crop type, and irrigation is critical for meeting nutritional needs sustainably. The United States has one of the most productive rainfed and irrigated croplands in the world and is a leading producer and exporter of agricultural crops. Precise maps of irrigated and rainfed croplands in the United States are crucial for assessing the current and the future agricultural production capacity in supporting food security. We developed a 30-m resolution rainfed and irrigated area map for the conterminous United States derived from 2019 to 2021 multi-date Landsat-8 data (LRIP30 CONUS 2020). A total of 96 harmonized spectral bands comprising monthly median value composites of eight bands (blue, green, red, NIR, SWIR1, SWIR2, TIR, and enhanced vegetation index [EVI]) were used. A cropland mask was then applied, and reference data were sourced from various sources. A pixel based supervised random forest classifier, and pixel based unsupervised ISODATA clustering classifier were implemented on Google Earth Engine and the ERDAS Imagine workstation to classify, identify, map, and assess accuracies of irrigated and rainfed cropland areas. The LRIP30 CONUS 2020 product achieved an overall accuracy of 93.9%. The irrigated and rainfed classes had producer's accuracies of 90.2% and 95.7%, respectively, and user's accuracies of 90.8% and 95.4%, respectively. The total net cropland area was estimated at 139.4 million hectares (Mha), of which 94.9 Mha (68%) was classified as rainfed and 44.5 Mha (32%) was classified as irrigated. State level summaries highlight regional differences and their implications for national and global food and water security.</span></p>","language":"English","publisher":"American Society for Photogrammetry and Remote Sensing","doi":"10.14358/PERS.25-00081R3","usgsCitation":"Teluguntla, P., Thenkabail, P., Oliphant, A., Aneece, I., Biggs, T., Murali Krishna Gumma, Foley, D., McCormick, R.L., Rohitha, N., Long, E., and Lawton, J., 2025, Landsat-derived rainfed and irrigated-area product for conterminous United States for the year 2020 (LRIP30 CONUS 2020) using supervised and unsupervised machine learning on the cloud: Photogrammetric Engineering & Remote Sensing, v. 91, no. 11, p. 703-714, https://doi.org/10.14358/PERS.25-00081R3.","productDescription":"12 p.","startPage":"703","endPage":"714","ipdsId":"IP-179081","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":498274,"rank":0,"type":{"id":40,"text":"Open Access Publisher 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,{"id":70272796,"text":"70272796 - 2025 - Freshwater turtle assemblages and densities in agricultural ditches and aquaculture ponds of eastern Arkansas","interactions":[],"lastModifiedDate":"2026-01-07T17:43:15.740234","indexId":"70272796","displayToPublicDate":"2025-10-31T09:00:11","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1210,"text":"Chelonian Conservation and Biology","active":true,"publicationSubtype":{"id":10}},"title":"Freshwater turtle assemblages and densities in agricultural ditches and aquaculture ponds of eastern Arkansas","docAbstract":"<p><span id=\"_mce_caret\" data-mce-bogus=\"1\" data-mce-type=\"format-caret\"><span>The Mississippi Alluvial Plain (MAP) of Arkansas is a landscape where many wetlands have been altered for use as aquaculture ponds or agricultural ditches. Commercial harvest of freshwater turtles within the MAP is not restricted or limited, with reported harvest numbers for 2019 alone exceeding 4000 for spiny softshell turtles (</span><i data-jats-toggle=\"yes\">Apalone spinifera</i><span>) and 39,000 for red-eared sliders (</span><i data-jats-toggle=\"yes\">Trachemys scripta elegans</i><span>). Herein, we attempt to provide baseline estimates of freshwater turtle densities and community composition in aquaculture ponds and agricultural ditches of eastern Arkansas, the habitat types most frequently trapped by commercial harvesters. We used a capture–mark–recapture approach over 3 summers (2019–2021) to evaluate population densities and community composition of freshwater turtles in these anthropogenic aquatic habitats. We captured &gt; 4000 individuals of 9 species of turtle. One species, the red-eared slider, dominated the turtle community in both anthropogenic aquatic habitats, comprising 66% (± 22% SD) of all captures in agricultural ditches and 63% (± 32% SD) in aquaculture ponds. Diversity and richness did not differ between aquaculture ponds and agricultural ditches. We estimated densities of the 2 most commonly captured species, the red-eared slider and spiny softshell turtle. Density of red-eared sliders ranged from 0 turtles/unit area (linear kilometers in ditches or hectares in ponds) to 500 turtles/unit area, with a median of 37 turtles/unit area. The spiny softshell turtle was more frequently captured in ponds than ditches and attained average densities of 25 (± 19) turtles/ha and 7 (± 4) turtles/linear km, respectively. Our mean density estimates were lower than those in reported literature, including estimates from similar habitats, such as urban ditches and farm ponds, which resemble our study sites in structure, use, and geographical placement. We estimate the region contains 22,317 ha of aquaculture ponds and 18,350 linear km of agricultural ditches. By extrapolating our density estimates to each anthropogenic aquatic habitat type, we estimated 2 million red-eared sliders and 427,000 spiny softshell turtles occurred in aquaculture ponds and agricultural ditches across eastern Arkansas. Our results suggest that these altered wetlands provide abundant habitat for only a few generalist turtle species.</span></span></p>","language":"English","publisher":"Chelonian Research Foundation","doi":"10.2744/CCB-1657","usgsCitation":"Massey, A.D., Willson, J.D., and DeGregorio, B.A., 2025, Freshwater turtle assemblages and densities in agricultural ditches and aquaculture ponds of eastern Arkansas: Chelonian Conservation and Biology, v. 24, no. 2, p. 247-259, https://doi.org/10.2744/CCB-1657.","productDescription":"13 p.","startPage":"247","endPage":"259","ipdsId":"IP-140476","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":498465,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.2744/ccb-1657","text":"Publisher Index Page"},{"id":497283,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arkansas","otherGeospatial":"eastern Arkansas","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -89.42194147233364,\n              36.49537693943422\n            ],\n            [\n              -90.53336912692878,\n              35.98215599237926\n            ],\n            [\n              -91.82405714395551,\n              32.97103287874471\n            ],\n            [\n              -91.11597605874528,\n              32.93341394306303\n            ],\n            [\n              -90.91430495911077,\n              33.87040325230258\n            ],\n            [\n              -90.04263999829463,\n              35.13890970234506\n            ],\n            [\n              -89.42194147233364,\n              36.49537693943422\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"24","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Massey, Andrhea D.","contributorId":363575,"corporation":false,"usgs":false,"family":"Massey","given":"Andrhea","middleInitial":"D.","affiliations":[{"id":6623,"text":"University of Arkansas","active":true,"usgs":false}],"preferred":false,"id":951798,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Willson, John D.","contributorId":363576,"corporation":false,"usgs":false,"family":"Willson","given":"John","middleInitial":"D.","affiliations":[{"id":6623,"text":"University of Arkansas","active":true,"usgs":false}],"preferred":false,"id":951799,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"DeGregorio, Brett Alexander 0000-0002-5273-049X","orcid":"https://orcid.org/0000-0002-5273-049X","contributorId":243214,"corporation":false,"usgs":true,"family":"DeGregorio","given":"Brett","email":"","middleInitial":"Alexander","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":951800,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70274551,"text":"70274551 - 2025 - An automated compositing method for producing annual clear images from Landsat Collection 2 for annual NLCD production","interactions":[],"lastModifiedDate":"2026-03-31T20:41:18.801907","indexId":"70274551","displayToPublicDate":"2025-10-24T15:36:40","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2027,"text":"International Journal of Applied Earth Observation and Geoinformation","active":true,"publicationSubtype":{"id":10}},"title":"An automated compositing method for producing annual clear images from Landsat Collection 2 for annual NLCD production","docAbstract":"<p><span>Quality image input is fundamental to the quality of derived land cover products. Substantial time and effort are usually required to prepare images. Here, we present a novel and streamlined compositing algorithm that ingests Landsat Collection 2 Analysis Ready Data (ARD) and outputs cloud-free and gap-free composite imagery, which can be directly used for classification. This method leverages and improves the previous National Land Cover Database (NLCD) Virtual Median Value Point (VMVP) compositing method, the first part of the image preparation for NLCD 2019 operational production. The NLCD 2019 image preparation approach includes a second part, a residual cloud and cloud shadow detection and gap-filling method, to produce final cloud-free and gap-free composite imagery. The second part requires one clear reference image for each target year. Additional reference images are needed for producing reasonable observations for perennial ice/snow areas because Pixel QA (Quality Assessment) from ARD has difficulties differentiating ice/snow areas from clouds. Unlike the NLCD 2019 image preparation approach, our new compositing method, which is referred to as Automated VMVP (AVMVP), uses Landsat ARD as the only input and does not require reference images and extra steps. In this method, we developed new spectral filter criteria coupled with counts of clear observations using Pixel QA to identify potential cloud and cloud shadow observations on initially selected observations from the NLCD VMVP compositing algorithm. We also automate “gap-filling” using clear observations retrieved from a maximum of ±2 years around the target year when needed. Finally, a percentile-filtered compositing method was developed for the perennial ice/snow areas. All these steps are streamlined, pixel-based, and directly run on Landsat Collection 2 ARD. We have run successful tests on the conterminous United States (CONUS). Composite images derived from our innovative method were used to produce the CONUS Annual NLCD Collection 1 product suite that covers the period from 1985 to 2023.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jag.2025.104920","usgsCitation":"Jin, S., Robinson, T., Dewitz, J., Smith, K., Danielson, P., and Postma, K., 2025, An automated compositing method for producing annual clear images from Landsat Collection 2 for annual NLCD production: International Journal of Applied Earth Observation and Geoinformation, v. 144, 104920, 17 p., https://doi.org/10.1016/j.jag.2025.104920.","productDescription":"104920, 17 p.","ipdsId":"IP-180439","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":502078,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jag.2025.104920","text":"Publisher Index Page"},{"id":501882,"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      \"type\": \"Feature\",\n      \"geometry\": {\n        \"type\": \"MultiPolygon\",\n        \"coordinates\": [\n          [\n            [\n              [\n                -94.81758,\n                49.38905\n              ],\n              [\n                -94.64,\n                48.84\n              ],\n              [\n                -94.32914,\n                48.67074\n              ],\n              [\n                -93.63087,\n                48.60926\n              ],\n              [\n                -92.61,\n                48.45\n              ],\n              [\n                -91.64,\n                48.14\n              ],\n              [\n                -90.83,\n                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]\n}","volume":"144","noUsgsAuthors":false,"publicationDate":"2025-10-24","publicationStatus":"PW","contributors":{"authors":[{"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":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":958257,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Robinson, Tonian","contributorId":369004,"corporation":false,"usgs":false,"family":"Robinson","given":"Tonian","affiliations":[{"id":87697,"text":"2Earth Space Technology, contractor to EROS","active":true,"usgs":false}],"preferred":false,"id":958258,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dewitz, Jon 0000-0002-0458-212X","orcid":"https://orcid.org/0000-0002-0458-212X","contributorId":215192,"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":958259,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Smith, Kelcy 0000-0001-6811-1485","orcid":"https://orcid.org/0000-0001-6811-1485","contributorId":272037,"corporation":false,"usgs":false,"family":"Smith","given":"Kelcy","affiliations":[{"id":56338,"text":"KBR, Inc., Contractor under USGS","active":true,"usgs":false}],"preferred":false,"id":958260,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Danielson, Patrick 0000-0002-2990-2783","orcid":"https://orcid.org/0000-0002-2990-2783","contributorId":302925,"corporation":false,"usgs":false,"family":"Danielson","given":"Patrick","affiliations":[{"id":65584,"text":"KBR, contractor to the USGS EROS","active":true,"usgs":false}],"preferred":false,"id":958261,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Postma, Kory 0000-0001-8058-498X","orcid":"https://orcid.org/0000-0001-8058-498X","contributorId":293879,"corporation":false,"usgs":false,"family":"Postma","given":"Kory","affiliations":[{"id":63548,"text":"KBRwyle, under contract to USGS","active":true,"usgs":false}],"preferred":false,"id":958262,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70272281,"text":"70272281 - 2025 - Control of a dominant predator influences the occurrence of a mesocarnivore of conservation concern","interactions":[],"lastModifiedDate":"2025-11-20T15:59:07.890196","indexId":"70272281","displayToPublicDate":"2025-10-24T09:53:32","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3777,"text":"Wildlife Research","active":true,"publicationSubtype":{"id":10}},"title":"Control of a dominant predator influences the occurrence of a mesocarnivore of conservation concern","docAbstract":"<div class=\"title\">Context</div><p>Interspecific interactions shape ecological communities, influence community dynamics, and drive co-evolution. Despite their ecological significance, predation and competition remain understudied in plains spotted skunks (<i>Spilogale interrupta</i>), a species of conservation concern. Clarifying how predator management influences their occurrence is crucial for effective conservation.</p><div class=\"title\">Aims</div><p>We investigated how coyote (<i>Canis latrans</i>) management affects the occupancy of plains spotted skunks and whether interspecific interactions with domestic cats (<i>Felis catus</i>) and striped skunks (<i>Mephitis mephitis</i>) influence plains spotted skunk occurrence.</p><div class=\"title\">Methods</div><p>We analysed live-trap data from east-central South Dakota collected in spring of 2021 and 2022. The study area encompassed portions of counties that implemented disparate predator management regimes, including one with systematic annual coyote removal and another without. We used single-species occupancy models to estimate detection and occupancy probabilities for plains spotted skunks, domestic cats, and striped skunks, incorporating environmental factors, including the site-specific predator control regime. We then applied conditional two-species occupancy models to test whether cats and striped skunks influenced plains spotted skunk occurrence.</p><div class=\"title\">Key results</div><p>Plains spotted skunks had the lowest occupancy, followed by domestic cats, and striped skunks. Our findings showed significant associations between coyote removal and occupancy probabilities for each mesocarnivore species. Plains spotted skunks had higher occupancy in areas where coyotes were annually removed. Spotted skunk occurrence was not conditional on either domestic cat or striped skunk occurrence.</p><div class=\"title\">Conclusions</div><p>In our study system, cats appear to pose less predation risk to spotted skunks than do other predators, reducing the likelihood that cats significantly influence spotted skunk occupancy. Defensive behaviours and use of spatial refugia by plains spotted skunks may further mitigate predation risk. In addition, co-evolutionary pressures may have led to trait adaptations that facilitate the independent co-occurrence of plains spotted skunks and striped skunks.</p><div class=\"title\">Implications</div><p>Our findings highlighted the ecological consequences of predator management and the importance of considering predator–prey dynamics in conservation and management planning. Strategies aimed at conserving plains spotted skunks should integrate predator control measures while considering broader mesocarnivore community interactions.</p>","language":"English","publisher":"CSIRO","doi":"10.1071/wr25116","usgsCitation":"White, K.M., Cheeseman, A.E., Stafford, J.D., and Lonsinger, R.C., 2025, Control of a dominant predator influences the occurrence of a mesocarnivore of conservation concern: Wildlife Research, v. 52, no. 11, WR25116, 11 p., https://doi.org/10.1071/wr25116.","productDescription":"WR25116, 11 p.","ipdsId":"IP-167639","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":496758,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1071/wr25116","text":"Publisher Index Page"},{"id":496689,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"South Dakota","county":"Faulk County, Hand County","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -99.41029196481595,\n              45.22348100024749\n            ],\n            [\n              -99.41029196481595,\n              44.93699850419435\n            ],\n            [\n              -99.21031756805021,\n              44.93699850419435\n            ],\n            [\n              -99.21031756805021,\n              45.22348100024749\n            ],\n            [\n              -99.41029196481595,\n              45.22348100024749\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -99.21800889100282,\n              44.862086955641644\n            ],\n            [\n              -99.21800889100282,\n              44.57653297552261\n            ],\n            [\n              -99.02572581718914,\n              44.57653297552261\n            ],\n            [\n              -99.02572581718914,\n              44.862086955641644\n            ],\n            [\n              -99.21800889100282,\n              44.862086955641644\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"52","issue":"11","noUsgsAuthors":false,"publicationDate":"2025-10-24","publicationStatus":"PW","contributors":{"authors":[{"text":"White, Kara M.","contributorId":362624,"corporation":false,"usgs":false,"family":"White","given":"Kara","middleInitial":"M.","affiliations":[{"id":5089,"text":"South Dakota State University","active":true,"usgs":false}],"preferred":false,"id":950668,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cheeseman, Amanda E.","contributorId":362627,"corporation":false,"usgs":false,"family":"Cheeseman","given":"Amanda","middleInitial":"E.","affiliations":[{"id":5089,"text":"South Dakota State University","active":true,"usgs":false}],"preferred":false,"id":950669,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stafford, Joshua D. 0000-0001-7590-8708 jstafford@usgs.gov","orcid":"https://orcid.org/0000-0001-7590-8708","contributorId":267260,"corporation":false,"usgs":true,"family":"Stafford","given":"Joshua","email":"jstafford@usgs.gov","middleInitial":"D.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":950670,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lonsinger, Robert Charles 0000-0002-1040-7299","orcid":"https://orcid.org/0000-0002-1040-7299","contributorId":340524,"corporation":false,"usgs":true,"family":"Lonsinger","given":"Robert","email":"","middleInitial":"Charles","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":950671,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70274146,"text":"70274146 - 2025 - Fish-assemblage and water-quality recovery with declining acidic deposition in Adirondack mountain streams, New York, USA","interactions":[],"lastModifiedDate":"2026-03-02T15:02:56.468026","indexId":"70274146","displayToPublicDate":"2025-10-24T07:54:49","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1699,"text":"Freshwater Science","active":true,"publicationSubtype":{"id":10}},"title":"Fish-assemblage and water-quality recovery with declining acidic deposition in Adirondack mountain streams, New York, USA","docAbstract":"<p><span id=\"_mce_caret\" data-mce-bogus=\"1\" data-mce-type=\"format-caret\"><span>Long-term records of air-pollutant emissions and atmospheric deposition, as well as water quality in streams of the Adirondack Mountains of New York, USA, indicate that chemical recovery from acidic deposition is progressing. Although Brook Trout&nbsp;</span><i>Salvelinus fontinalis</i><span>&nbsp;(Mitchill, 1814) have recently repopulated several lakes, the degree to which fish assemblages and individual species populations have recovered in streams of the region is unknown. The United States Geological Survey sampled acid–base chemistry and fish assemblages at 42 Adirondack region streams (2014–2021), most of which were also sampled in 2 prior periods (primarily 1979–1984 and 1999), to determine the extent and degree of chemical and biological recovery and whether responses could be linked to regional declines in acidic deposition. Between 1990 and 2021, total annual emissions of SO</span><sub>2</sub><span>&nbsp;and NO</span><sub><i>x</i></sub><span>&nbsp;declined nationwide by 94% and 87%, respectively, and paralleled 88% and 70% decreases in SO</span><sub>4</sub><sup>2−</sup><span>&nbsp;and NO</span><sub>3</sub><sup>−</sup><span>&nbsp;concentrations, respectively, in wet deposition in the region. During this interval, mean acid neutralizing capacity increased by 19.9 µeq/L, pH increased by 0.33 units, and inorganic Al (Al</span><sub>i</sub><span>) decreased by 6.0 µmol/L at one continuously monitored stream, whereas mean acid neutralizing capacity increased by 38.5 µeq/L and mean Al</span><sub>i</sub><span>&nbsp;concentration decreased by ∼3.0 µmol/L during springtime at all 42 Adirondack region streams. Between the 1</span><sup>st</sup><span>&nbsp;and 3</span><sup>rd</sup><span>&nbsp;periods, mean fish-assemblage richness, density, and biomass at 40 sites increased by 112%, 236%, and 66%, respectively. Although mean Brook Trout density and biomass did not meaningfully change among periods, their distribution expanded from 20 sites in the strongly impacted sampling period (1979–1984) to 33 sites in the recovery period (2014–2021). Trends in pollutant emissions and deposition, water quality, and fish-assemblage metrics indicate aquatic ecosystems in many Adirondack mountain streams improved markedly following implementation of the 1990 Clean Air Act Amendments and recent N and S allowance-trading and emissions regulations.</span></span></p>","language":"English","publisher":"University of Chicago Press","doi":"10.1086/738871","usgsCitation":"Baldigo, B.P., George, S.D., and Lawrence, G.B., 2025, Fish-assemblage and water-quality recovery with declining acidic deposition in Adirondack mountain streams, New York, USA: Freshwater Science, v. 44, no. 4, p. 443-462, https://doi.org/10.1086/738871.","productDescription":"20 p.","startPage":"443","endPage":"462","ipdsId":"IP-154992","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":500670,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Adirondack State Park","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -75.26665751178325,\n              44.60507553722792\n            ],\n            [\n              -75.65331217554504,\n              44.14950624058149\n            ],\n            [\n              -75.15224396884794,\n              43.1190030583347\n            ],\n            [\n              -73.96958415264136,\n              42.98169264950411\n            ],\n            [\n              -73.26534654292884,\n              43.78514049152075\n            ],\n            [\n              -73.34519835014197,\n              44.82227470192748\n            ],\n            [\n              -74.42802264458987,\n              44.85423999436294\n            ],\n            [\n              -75.26665751178325,\n              44.60507553722792\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"44","issue":"4","edition":"2025","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Baldigo, Barry P. 0000-0002-9862-9119 bbaldigo@usgs.gov","orcid":"https://orcid.org/0000-0002-9862-9119","contributorId":221408,"corporation":false,"usgs":true,"family":"Baldigo","given":"Barry","email":"bbaldigo@usgs.gov","middleInitial":"P.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":956683,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"George, Scott D. 0000-0002-8197-1866 sgeorge@usgs.gov","orcid":"https://orcid.org/0000-0002-8197-1866","contributorId":3014,"corporation":false,"usgs":true,"family":"George","given":"Scott","email":"sgeorge@usgs.gov","middleInitial":"D.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":956684,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lawrence, Gregory B. 0000-0002-8035-2350 glawrenc@usgs.gov","orcid":"https://orcid.org/0000-0002-8035-2350","contributorId":214242,"corporation":false,"usgs":true,"family":"Lawrence","given":"Gregory","email":"glawrenc@usgs.gov","middleInitial":"B.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":956685,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70272160,"text":"70272160 - 2025 - Greenhouse gas emissions from ditches in oil palm plantations on tropical peatlands in Malaysia","interactions":[],"lastModifiedDate":"2025-11-18T15:20:15.149263","indexId":"70272160","displayToPublicDate":"2025-10-23T08:15:41","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3358,"text":"Scientific Reports","active":true,"publicationSubtype":{"id":10}},"title":"Greenhouse gas emissions from ditches in oil palm plantations on tropical peatlands in Malaysia","docAbstract":"<p><span>Tropical peatlands, which store 20% of global peat carbon, are increasingly threatened by conversion to alternative land-uses such as oil palm plantations, pulp wood plantations, crop growth or other economic activities. This transformation involves peatland drainage, which lowers water tables, exposes peat to oxygen, and alters greenhouse gas (GHG) emissions: increasing carbon dioxide (CO</span><sub>2</sub><span>) and nitrous oxide (N</span><sub>2</sub><span>O) fluxes while reducing methane (CH</span><sub>4</sub><span>) emissions from soils. However, drainage ditches created in the process may become significant sources of CH</span><sub>4</sub><span>&nbsp;due to anoxic conditions. This study quantified GHG fluxes from drainage ditches in Sarawak, Malaysia, through spatial sampling conducted during the daytime in the transitional period between the drier and wetter seasons using portable trace gas analyzers. Median fluxes were 0.19&nbsp;g CH</span><sub>4</sub><span>&nbsp;m</span><sup>−2</sup><span>&nbsp;d</span><sup>−1</sup><span>, 17.1&nbsp;g CO</span><sub>2</sub><span>&nbsp;m</span><sup>−2</sup><span>&nbsp;d</span><sup>−1</sup><span>, and − 0.12&nbsp;mg N</span><sub>2</sub><span>O m</span><sup>−2</sup><span>&nbsp;d</span><sup>−1</sup><span>. Physical water parameters such as pH, oxygen concentration, temperature, and oxidation–reduction potential were found to be significant drivers of GHG fluxes. The median emissions from ditches in one hectare of land were 5.84&nbsp;kg CO</span><sub>2</sub><span>&nbsp;ha</span><sup>−1</sup><span>&nbsp;d</span><sup>−1</sup><span>, 2.78&nbsp;kg CH</span><sub>4</sub><span>&nbsp;as CO</span><sub>2</sub><span>&nbsp;eq ha</span><sup>−1</sup><span>&nbsp;d</span><sup>−1</sup><span>, and − 0.001&nbsp;kg N</span><sub>2</sub><span>O as CO</span><sub>2</sub><span>&nbsp;eq ha</span><sup>−1</sup><span>&nbsp;d</span><sup>−1</sup><span>. These findings underscore the role of drainage ditches as CH</span><sub>4</sub><span>&nbsp;sources in tropical peatland agriculture, highlighting the need for further research into GHG management in these modified landscapes.</span></p>","language":"English","publisher":"Springer Nature","doi":"10.1038/s41598-025-21094-3","usgsCitation":"Kasak, K., Dronova, I., Soosaar, K., Melling, L., Xhuan, W.G., Sangok, F., Ranniku, R., Villa, J.A., Bansal, S., Peacock, M., and Mander, Ü., 2025, Greenhouse gas emissions from ditches in oil palm plantations on tropical peatlands in Malaysia: Scientific Reports, v. 15, 37126, 13 p., https://doi.org/10.1038/s41598-025-21094-3.","productDescription":"37126, 13 p.","ipdsId":"IP-170583","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":496731,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-025-21094-3","text":"Publisher Index Page"},{"id":496583,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Malaysia","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              99.99937723563403,\n              6.756461538667807\n            ],\n            [\n              99.99937723563403,\n              2.710494555037542\n            ],\n            [\n              103.80214382028282,\n              2.710494555037542\n            ],\n            [\n              103.80214382028282,\n              6.756461538667807\n            ],\n            [\n              99.99937723563403,\n              6.756461538667807\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"15","noUsgsAuthors":false,"publicationDate":"2025-10-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Kasak, Kuno","contributorId":265844,"corporation":false,"usgs":false,"family":"Kasak","given":"Kuno","email":"","affiliations":[],"preferred":false,"id":950274,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dronova, Iryna 0000-0003-3339-3704","orcid":"https://orcid.org/0000-0003-3339-3704","contributorId":272607,"corporation":false,"usgs":false,"family":"Dronova","given":"Iryna","email":"","affiliations":[{"id":6609,"text":"UC Berkeley","active":true,"usgs":false}],"preferred":false,"id":950275,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Soosaar, Kaido","contributorId":362287,"corporation":false,"usgs":false,"family":"Soosaar","given":"Kaido","affiliations":[],"preferred":false,"id":950276,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Melling, Lulie","contributorId":260542,"corporation":false,"usgs":false,"family":"Melling","given":"Lulie","email":"","affiliations":[],"preferred":false,"id":950277,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Xhuan, Wong Guan","contributorId":362288,"corporation":false,"usgs":false,"family":"Xhuan","given":"Wong","middleInitial":"Guan","affiliations":[],"preferred":false,"id":950278,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sangok, Faustina","contributorId":362290,"corporation":false,"usgs":false,"family":"Sangok","given":"Faustina","affiliations":[],"preferred":false,"id":950279,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ranniku, Reti","contributorId":362292,"corporation":false,"usgs":false,"family":"Ranniku","given":"Reti","affiliations":[],"preferred":false,"id":950280,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Villa, Jorge A.","contributorId":362293,"corporation":false,"usgs":false,"family":"Villa","given":"Jorge","middleInitial":"A.","affiliations":[],"preferred":false,"id":950281,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Bansal, Sheel 0000-0003-1233-1707 sbansal@usgs.gov","orcid":"https://orcid.org/0000-0003-1233-1707","contributorId":167295,"corporation":false,"usgs":true,"family":"Bansal","given":"Sheel","email":"sbansal@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":950282,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Peacock, Michael","contributorId":362298,"corporation":false,"usgs":false,"family":"Peacock","given":"Michael","affiliations":[],"preferred":false,"id":950283,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Mander, Ülo","contributorId":362300,"corporation":false,"usgs":false,"family":"Mander","given":"Ülo","affiliations":[],"preferred":false,"id":950284,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}}
,{"id":70272449,"text":"70272449 - 2025 - Expression and mechanisms of behavioral plasticity in large mammals","interactions":[],"lastModifiedDate":"2025-11-21T18:21:10.277585","indexId":"70272449","displayToPublicDate":"2025-10-20T12:05:47","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Expression and mechanisms of behavioral plasticity in large mammals","docAbstract":"<p><span>Behavioral plasticity, the alteration of behavior in response to stimuli, is becoming increasingly important in the context of human-induced rapid environmental change. Theoretical and empirical studies suggest that the expression and magnitude of behavioral plasticity are likely facilitated or constrained primarily by two factors: environmental variation and endogenous traits such as body size. The contextual role of these factors on behavioral plasticity, however, is poorly understood; there are relatively few studies that have compared the magnitude and potential drivers of behavioral plasticity at different levels (i.e., population and individual) across species, especially in free-ranging animals with diverse behavioral traits such as large mammals. Here, we quantify and test potential hypotheses for the mechanisms underpinning behavioral plasticity at the individual and population level in response to variation in summer temperatures for 1068 animal-years in 17 populations across nine species of large mammals. All populations displayed behavioral plasticity in response to increased temperatures, modifying their relative selection for heat-relieving habitat attributes (e.g., elevation) and heat-generating behavior (i.e., movement speed). We found strong support for the hypothesis that the variability of the physical environment is an important driver of behavioral plasticity—both mean population behavioral plasticity and variation among individuals within each population in plasticity were lower with increased heterogeneity of habitat attributes such as tree cover. Yet, the variability in environmental conditions (i.e., the magnitude of the temperature increase) had no effect on behavioral plasticity within and among populations. We did not detect an effect of endogenous traits on the expression of behavioral plasticity; however, we note that data availability limited our tests of this hypothesis to a select few endogenous traits (body size, feeding guild, and sex of the tracked individuals) that predominantly vary at the species level, for which we had one to three replicate populations per species. Our results provide an integrative and generalizable understanding of the expression of behavioral plasticity among populations of large mammals in temperate environments and emphasize the important but nuanced role of environmental variation in determining the scope of behavioral plasticity in these populations.</span></p>","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.70432","usgsCitation":"Thomas-Kuzilik, R.R., Becker, J.A., Beck, J.L., Clapp, J.G., Courtemanch, A.B., Fralick, G.L., Geremia, C., Hall, L.E., Kauffman, M., Lowrey, B., Metz, M.C., Miyasaki, H.M., Monteith, K.L., Ortega, A.C., Sawyer, H., Smith, D.W., Stahler, E.E., Stahler, D.R., Verzuh, T.L., and Merkle, J.A., 2025, Expression and mechanisms of behavioral plasticity in large mammals: Ecosphere, v. 16, no. 10, e70432, 27 p., https://doi.org/10.1002/ecs2.70432.","productDescription":"e70432, 27 p.","ipdsId":"IP-165914","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":496922,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.70432","text":"Publisher Index Page"},{"id":496782,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -111.05444391365384,\n              44.981739589770086\n            ],\n            [\n              -111.05444391365384,\n              41.00306317425938\n            ],\n            [\n              -104.09549358601788,\n              41.00306317425938\n            ],\n            [\n              -104.09549358601788,\n              44.981739589770086\n            ],\n            [\n              -111.05444391365384,\n              44.981739589770086\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"16","issue":"10","noUsgsAuthors":false,"publicationDate":"2025-10-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Thomas-Kuzilik, Rebecca R.","contributorId":362836,"corporation":false,"usgs":false,"family":"Thomas-Kuzilik","given":"Rebecca","middleInitial":"R.","affiliations":[],"preferred":false,"id":950754,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Becker, Justine A.","contributorId":362837,"corporation":false,"usgs":false,"family":"Becker","given":"Justine","middleInitial":"A.","affiliations":[],"preferred":false,"id":950755,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Beck, Jeffrey L.","contributorId":287806,"corporation":false,"usgs":false,"family":"Beck","given":"Jeffrey","middleInitial":"L.","affiliations":[{"id":12729,"text":"UW","active":true,"usgs":false}],"preferred":false,"id":950831,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Clapp, Justin G.","contributorId":362838,"corporation":false,"usgs":false,"family":"Clapp","given":"Justin","middleInitial":"G.","affiliations":[],"preferred":false,"id":950756,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Courtemanch, Alyson B.","contributorId":362839,"corporation":false,"usgs":false,"family":"Courtemanch","given":"Alyson","middleInitial":"B.","affiliations":[],"preferred":false,"id":950757,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Fralick, Gary L.","contributorId":362840,"corporation":false,"usgs":false,"family":"Fralick","given":"Gary","middleInitial":"L.","affiliations":[],"preferred":false,"id":950758,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Geremia, Chris","contributorId":362841,"corporation":false,"usgs":false,"family":"Geremia","given":"Chris","affiliations":[],"preferred":false,"id":950759,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hall, L. Embere","contributorId":362842,"corporation":false,"usgs":false,"family":"Hall","given":"L.","middleInitial":"Embere","affiliations":[],"preferred":false,"id":950760,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Kauffman, Matthew J. 0000-0003-0127-3900","orcid":"https://orcid.org/0000-0003-0127-3900","contributorId":210786,"corporation":false,"usgs":true,"family":"Kauffman","given":"Matthew","middleInitial":"J.","affiliations":[{"id":484,"text":"Northwest Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":950761,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Lowrey, Blake 0000-0002-4994-2117","orcid":"https://orcid.org/0000-0002-4994-2117","contributorId":335494,"corporation":false,"usgs":true,"family":"Lowrey","given":"Blake","email":"","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":950753,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Metz, Matthew C.","contributorId":362843,"corporation":false,"usgs":false,"family":"Metz","given":"Matthew","middleInitial":"C.","affiliations":[],"preferred":false,"id":950762,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Miyasaki, Hollie M.","contributorId":362844,"corporation":false,"usgs":false,"family":"Miyasaki","given":"Hollie","middleInitial":"M.","affiliations":[],"preferred":false,"id":950763,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Monteith, Kevin L.","contributorId":362845,"corporation":false,"usgs":false,"family":"Monteith","given":"Kevin","middleInitial":"L.","affiliations":[],"preferred":false,"id":950764,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Ortega, Anna C.","contributorId":362846,"corporation":false,"usgs":false,"family":"Ortega","given":"Anna","middleInitial":"C.","affiliations":[],"preferred":false,"id":950765,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Sawyer, Hall","contributorId":362847,"corporation":false,"usgs":false,"family":"Sawyer","given":"Hall","affiliations":[],"preferred":false,"id":950766,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Smith, Douglas W.","contributorId":362848,"corporation":false,"usgs":false,"family":"Smith","given":"Douglas","middleInitial":"W.","affiliations":[],"preferred":false,"id":950767,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Stahler, Erin E.","contributorId":362849,"corporation":false,"usgs":false,"family":"Stahler","given":"Erin","middleInitial":"E.","affiliations":[],"preferred":false,"id":950768,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Stahler, Daniel R.","contributorId":362850,"corporation":false,"usgs":false,"family":"Stahler","given":"Daniel","middleInitial":"R.","affiliations":[],"preferred":false,"id":950769,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Verzuh, Tana L.","contributorId":362851,"corporation":false,"usgs":false,"family":"Verzuh","given":"Tana","middleInitial":"L.","affiliations":[],"preferred":false,"id":950770,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Merkle, Jerod A.","contributorId":362852,"corporation":false,"usgs":false,"family":"Merkle","given":"Jerod","middleInitial":"A.","affiliations":[],"preferred":false,"id":950771,"contributorType":{"id":1,"text":"Authors"},"rank":20}]}}
,{"id":70272172,"text":"70272172 - 2025 - Re-oligotrophy in the Upper Mississippi River, USA, occurred in just a few years","interactions":[],"lastModifiedDate":"2025-12-15T16:40:30.851106","indexId":"70272172","displayToPublicDate":"2025-10-15T09:08:07","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1699,"text":"Freshwater Science","active":true,"publicationSubtype":{"id":10}},"title":"Re-oligotrophy in the Upper Mississippi River, USA, occurred in just a few years","docAbstract":"<p><span>Ecological systems can undergo large changes and regime shifts that are either catastrophic, neutral, or desirable. Rivers worldwide have recently undergone desirable regime shifts related to re-oligotrophy, which is a notable and ongoing reduction in concentrations of total suspended solids (TSS), total N, total P, or phytoplankton. For example, the Upper Mississippi River, USA, has experienced major water-quality changes in multiple river reaches in recent decades. In this study, we sought to understand the timing and magnitude of re-oligotrophy in the Mississippi River over a 20-y period. We used 2 topological data analysis algorithms to address hypotheses related to the following questions: What were the order and timing of water-quality changes? What was the time period over which the major changes occurred? What was the magnitude of water-quality change before and after change points (i.e., specific years when water-quality conditions transitioned abruptly to new states)? We examined 6 water-quality state variables that defined the ecological regime for the Upper Mississippi River. In one river reach, we found that strong reductions in phytoplankton/chlorophyll&nbsp;</span><i>a</i><span>&nbsp;had occurred first (2008), followed by total P (2013), and last in TSS (2014). In a downriver reach, we found notable reductions for chlorophyll&nbsp;</span><i>a</i><span>&nbsp;(2007) but substantial increases in TSS (2013). In both reaches, the water-quality changes trended over ≥15 y, but the largest changes and a likely regime shift occurred in just 6 y. The timing (2007–2014) and range (~6 y) of water-quality changes were similar between the 2 river reaches, but the directionality of the regime shift indicated re-oligotrophy for the upstream reach and water-quality degradation for the downstream reach. Topological methods applied to long-term datasets can aid our understanding of re-oligotrophication and degradation processes and may help resource managers restore desirable regimes.</span></p>","language":"English","publisher":"University of Chicago Press","doi":"10.1086/738457","usgsCitation":"Davis, K., Bungula, W., and Larson, D.M., 2025, Re-oligotrophy in the Upper Mississippi River, USA, occurred in just a few years: Freshwater Science, v. 44, no. 4, p. 409-421, https://doi.org/10.1086/738457.","productDescription":"13 p.","startPage":"409","endPage":"421","ipdsId":"IP-158399","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":496580,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"44","issue":"4","noUsgsAuthors":false,"publicationDate":"2025-10-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Davis, Killian","contributorId":315371,"corporation":false,"usgs":false,"family":"Davis","given":"Killian","email":"","affiliations":[{"id":68293,"text":"University of Wisconsin La Crosse","active":true,"usgs":false}],"preferred":false,"id":950301,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bungula, Wako","contributorId":315367,"corporation":false,"usgs":false,"family":"Bungula","given":"Wako","email":"","affiliations":[{"id":68293,"text":"University of Wisconsin La Crosse","active":true,"usgs":false}],"preferred":false,"id":950302,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Larson, Danelle M. 0000-0001-6349-6267","orcid":"https://orcid.org/0000-0001-6349-6267","contributorId":228838,"corporation":false,"usgs":true,"family":"Larson","given":"Danelle","email":"","middleInitial":"M.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":950303,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
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