Many mountain belts are built through repeated collision, and in the case of orogenies closely spaced in time, determining when one orogeny ends and another begins can be challenging. The southern Appalachian mountains were formed by three mountain-building events closely spaced in time, including the Taconic (ca. 480–440 Ma), Neoacadian (ca. 375–340 Ma), and Alleghanian (ca. 330–265 Ma) orogenies. Notably, the end of the Neoacadian and the beginning of the Alleghanian are only separated by ~10 m.y., and some published dates record deformation and metamorphism in the eastern Blue Ridge during this interval, blurring the boundary between these two discrete events.
The Toxaway dome, located along the North Carolina–South Carolina, USA, border at the eastern edge of the eastern Blue Ridge, is a structural dome cored by Mesoproterozoic Toxaway Gneiss and surrounded by the younger Tallulah Falls Formation. Previous ages constraints from the Toxaway dome (343 and 338 Ma U-Pb zircon ages) make it an ideal location to explore whether there was continuous deformation during this period of supposed quiescence between the Neoacadian and Alleghanian orogenies. We used optical microscopy and electron backscatter diffraction in quartz to determine deformation temperatures, thermobarometry to determine metamorphic pressure-temperature conditions, and monazite petrochronology to determine the timing of deformation. Quartz and feldspar recrystallization fabrics parallel to dome-defining fabrics indicate deformation occurred at amphibolite-facies conditions, which is corroborated by our pressure-temperature estimates of 0.67–0.8 ± 0.12 GPa and 661–689 ± 25 °C. Monazite grains that record the timing of reactions of garnet growth and breakdown range from 342 ± 4.8 Ma to 296 ± 10.8 Ma, bridging the interval between the Neoacadian and Alleghanian orogenies. Three samples from the nearby Tallulah Falls dome, which occupies a similar structural position along the edge of the eastern Blue Ridge in Georgia, record monazite dates of 334 ± 4.2 Ma to 304 ± 4.8 Ma, indicating there was tectonic activity in this region before the commonly defined beginning of the Alleghanian orogeny. We propose (1) there was no period of quiescence between the Neoacadian and Alleghanian orogenies in the eastern Blue Ridge, and (2) deformation during this time was at higher temperatures and pressures than previously reported.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/GES02802.1","usgsCitation":"Levine, J., Powell, N.E., Casale, G., and Martin, C., 2025, Timing of and pressure-temperature constraints on deformation in the Toxaway dome, eastern Blue Ridge: Evidence for continuous deformation from the Neoacadian orogeny to the Alleghanian orogeny: Geosphere, v. 21, no. 2, p. 179-205, https://doi.org/10.1130/GES02802.1.","productDescription":"27 p.","startPage":"179","endPage":"205","ipdsId":"IP-166597","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":488667,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/ges02802.1","text":"Publisher Index Page"},{"id":483881,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Georgia, North Carolina, South Carolina","otherGeospatial":"Tallulah Fault Dome, Toxaway Dome","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -82.12768324273705,\n 36.09919315340798\n ],\n [\n -84.53940674334677,\n 36.09919315340798\n ],\n [\n -84.53940674334677,\n 33.93940700100836\n ],\n [\n -82.12768324273705,\n 33.93940700100836\n ],\n [\n -82.12768324273705,\n 36.09919315340798\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"21","issue":"2","noUsgsAuthors":false,"publicationDate":"2025-01-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Levine, Jamie S.F. 0000-0003-4100-6428","orcid":"https://orcid.org/0000-0003-4100-6428","contributorId":352688,"corporation":false,"usgs":false,"family":"Levine","given":"Jamie S.F.","affiliations":[{"id":36626,"text":"Appalachian State University","active":true,"usgs":false}],"preferred":false,"id":932007,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Powell, Nicholas Edwin 0000-0003-3654-8759","orcid":"https://orcid.org/0000-0003-3654-8759","contributorId":304622,"corporation":false,"usgs":true,"family":"Powell","given":"Nicholas","email":"","middleInitial":"Edwin","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":932008,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Casale, Gabriele 0000-0003-1371-753X","orcid":"https://orcid.org/0000-0003-1371-753X","contributorId":192726,"corporation":false,"usgs":false,"family":"Casale","given":"Gabriele","email":"","affiliations":[{"id":27675,"text":"Appalachian State University, Boone, NC","active":true,"usgs":false}],"preferred":false,"id":932009,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Martin, Claire P. 0000-0001-8813-5070","orcid":"https://orcid.org/0000-0001-8813-5070","contributorId":352689,"corporation":false,"usgs":false,"family":"Martin","given":"Claire P.","affiliations":[{"id":84283,"text":"StraboSpot, Texas A&M University","active":true,"usgs":false}],"preferred":false,"id":932010,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70262522,"text":"70262522 - 2025 - From subsidies to stressors: Shifting ecological baselines alter biological responses to nutrients in highly modified agricultural streams","interactions":[],"lastModifiedDate":"2025-01-22T14:45:54.773366","indexId":"70262522","displayToPublicDate":"2025-01-17T09:57:09","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"From subsidies to stressors: Shifting ecological baselines alter biological responses to nutrients in highly modified agricultural streams","docAbstract":"Subsidy–stress gradients offer a useful framework for understanding ecological responses to perturbation and may help inform ecological metrics in highly modified systems. Historic, region-wide shifts from bottomland hardwood forest to row crop agriculture can cause positively skewed impact gradients in alluvial plain ecoregions, resulting in tolerant organisms that typically exhibit a subsidy response (increased abundance in response to environmental stressors) shifting to a stress response (declining abundance at higher concentrations). As a result, observed biological tolerance in modified ecosystems may differ from less modified regions, creating significant challenges for detecting biological responses to restoration efforts. Using the agriculturally dominated Mississippi Alluvial Plain (MAP) ecoregion in Mississippi, USA, as a case study, we tested the hypothesis that macroinvertebrate taxa that typically display a subsidy response to nutrient enrichment in less modified ecoregions (i.e., nutrient-tolerance) shift to a stress response to increasing nutrients in highly modified watersheds with elevated baseline nutrient conditions (i.e., nutrient intolerance). The abundance and diversity of MAP-specific intolerant taxa identified with threshold indicator taxa analysis were either unresponsive or exhibited a subsidy response to increasing nutrients in less modified ecoregions in Mississippi with less land alteration and lower nutrient concentrations, but declined at higher concentrations, providing evidence for a stress response to elevated nutrients in the MAP. Additionally, MAP-specific tolerant and intolerant taxa richness responded to increased nutrients predictably and consistently across space and time within the MAP. However, in MAP streams, elevated specific conductance was predicted to dampen the response of tolerant and intolerant taxa richness to increasing nutrient concentrations, highlighting the importance of considering multistressor interactions when interpreting biological data. Lastly, we demonstrate the efficacy of this approach with sediment bacterial communities characterized with amplicon sequencing, which lack sufficient life history characteristics necessary for the development of multimetric indices. Both macroinvertebrate and bacterial communities responded similarly to increasing nutrient concentrations, suggesting DNA-based approaches may provide an efficient biological assessment tool for monitoring water quality improvements in highly modified watersheds.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/eap.3086","usgsCitation":"Devilbiss, S., Taylor, J., and Hicks, M.B., 2025, From subsidies to stressors: Shifting ecological baselines alter biological responses to nutrients in highly modified agricultural streams: Ecological Applications, v. 35, no. 1, e3086, 21 p., https://doi.org/10.1002/eap.3086.","productDescription":"e3086, 21 p.","ipdsId":"IP-159539","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":481027,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/eap.3086","text":"Publisher Index Page"},{"id":480830,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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\"}}]}","volume":"35","issue":"1","noUsgsAuthors":false,"publicationDate":"2025-01-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Devilbiss, Stephen Edward 0000-0002-3512-2505","orcid":"https://orcid.org/0000-0002-3512-2505","contributorId":343984,"corporation":false,"usgs":true,"family":"Devilbiss","given":"Stephen Edward","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":924442,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Taylor, Jason M. 0000-0001-9240-2151","orcid":"https://orcid.org/0000-0001-9240-2151","contributorId":343985,"corporation":false,"usgs":false,"family":"Taylor","given":"Jason M.","affiliations":[{"id":6758,"text":"USDA-ARS","active":true,"usgs":false}],"preferred":false,"id":924443,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hicks, Matthew B. 0000-0001-5516-0296 mhicks@usgs.gov","orcid":"https://orcid.org/0000-0001-5516-0296","contributorId":3778,"corporation":false,"usgs":true,"family":"Hicks","given":"Matthew","email":"mhicks@usgs.gov","middleInitial":"B.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":924444,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70264116,"text":"70264116 - 2025 - New 40Ar/39Ar eruption ages reveal an important temporal relationship between mafic and silicic volcanism in the Yellowstone Plateau volcanic field","interactions":[],"lastModifiedDate":"2025-04-17T15:34:45.630531","indexId":"70264116","displayToPublicDate":"2025-01-17T09:50:38","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1796,"text":"Geology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"New 40Ar/39Ar eruption ages reveal an important temporal relationship between mafic and silicic volcanism in the Yellowstone Plateau volcanic field","title":"New 40Ar/39Ar eruption ages reveal an important temporal relationship between mafic and silicic volcanism in the Yellowstone Plateau volcanic field","docAbstract":"The chronology of mafic eruptions and their temporal relation to rhyolitic volcanism in the Yellowstone Plateau volcanic field are poorly known, thereby limiting our understanding of the way(s) in which mafic magmatism drives rhyolitic activity. To address this, we measured 40Ar/39Ar eruption ages on 13 mafic samples collected from Henrys Fork Caldera (eastern Idaho, western United States), which represents a region of known volcanic activity immediately west of Yellowstone caldera for which the relationship to Yellowstone volcano’s most recent caldera-forming cycle remains unclear. Our new ages indicate that mafic activity was occurring throughout the Henrys Fork Caldera both leading up to and following the emplacement of the Lava Creek Tuff. Furthermore, these ages reveal that mafic volcanism in the Henrys Fork Caldera region occurred concurrently with second- and third-cycle rhyolite volcanism in and around Yellowstone caldera. Our new ages therefore provide unique and definitive evidence that the mafic magmatism of Henrys Fork Caldera played a critical role in the development of shallow-crustal rhyolitic magma chambers that ultimately fueled the large caldera-forming eruptions within the Yellowstone volcanic system.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/G52709.1","usgsCitation":"Messa, C., Sims, K., Stelten, M.E., Lawler, B., and Kuntz, M., 2025, New 40Ar/39Ar eruption ages reveal an important temporal relationship between mafic and silicic volcanism in the Yellowstone Plateau volcanic field: Geology, v. 53, no. 4, p. 317-322, https://doi.org/10.1130/G52709.1.","productDescription":"6 p.","startPage":"317","endPage":"322","ipdsId":"IP-165883","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":482974,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho","otherGeospatial":"Henry's Fork Caldera","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -111.1667,\n 44.5\n ],\n [\n -111.8333,\n 44.5\n ],\n [\n -111.8333,\n 44 \n ],\n [\n -111.1667,\n 44\n ],\n [\n -111.1667,\n 44.5\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"53","issue":"4","noUsgsAuthors":false,"publicationDate":"2025-01-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Messa, Cole","contributorId":351999,"corporation":false,"usgs":false,"family":"Messa","given":"Cole","affiliations":[{"id":36628,"text":"University of Wyoming","active":true,"usgs":false}],"preferred":false,"id":929874,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sims, Kenneth 0000-0001-6179-6610","orcid":"https://orcid.org/0000-0001-6179-6610","contributorId":352001,"corporation":false,"usgs":false,"family":"Sims","given":"Kenneth","affiliations":[{"id":36628,"text":"University of Wyoming","active":true,"usgs":false}],"preferred":false,"id":929875,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stelten, Mark E. 0000-0002-5294-3161 mstelten@usgs.gov","orcid":"https://orcid.org/0000-0002-5294-3161","contributorId":145923,"corporation":false,"usgs":true,"family":"Stelten","given":"Mark","email":"mstelten@usgs.gov","middleInitial":"E.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":929876,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lawler, Brandi","contributorId":352004,"corporation":false,"usgs":false,"family":"Lawler","given":"Brandi","affiliations":[{"id":36628,"text":"University of Wyoming","active":true,"usgs":false}],"preferred":false,"id":929877,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kuntz, Mel","contributorId":352007,"corporation":false,"usgs":false,"family":"Kuntz","given":"Mel","affiliations":[{"id":37374,"text":"Retired USGS","active":true,"usgs":false}],"preferred":false,"id":929878,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70267792,"text":"70267792 - 2025 - Variation in habitat selection by male Strix nebulosa (Great Gray Owls) across the diel cycle","interactions":[],"lastModifiedDate":"2025-06-02T15:37:53.643622","indexId":"70267792","displayToPublicDate":"2025-01-17T08:32:57","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":10109,"text":"Ornithology","active":true,"publicationSubtype":{"id":10}},"title":"Variation in habitat selection by male Strix nebulosa (Great Gray Owls) across the diel cycle","docAbstract":"Despite the long-standing recognition that animals partition activities, for example, across different periods of the day, understanding of how habitat selection varies according to specific temporal periods or behavioral activities remains limited for most species. For example, although much of the animal kingdom is nocturnally active, studies that characterize nocturnal behavior remain relatively rare, which precludes a thorough understanding of key habitats. We used Global Positioning System tracking and remotely-sensed environmental data to evaluate whether breeding-season habitat selection by adult male Strix nebulosa (Great Gray Owls) (n = 19) varied across diel periods (dawn, day, dusk, and night). We focused on male owls because their habitat selection remains largely unknown despite the critical role they play as food provisioners. To address knowledge gaps related to nocturnal habitat, we also evaluated finer-scale, microhabitat selection by male owls at night. Owls were more active during dusk through dawn, suggesting that owls forage during crepuscular and nighttime periods and roost during the day. Owls avoided herbaceous wetlands during the day but strongly selected them at dawn, dusk, and night, indicating time-dependent habitat selection. Moreover, owls avoided dry meadows at all times of the day, suggesting that wet rather than xeric meadows are important for foraging. Owls also selected nighttime microhabitats that facilitated foraging, such as those with the presence of primary prey and open understories. During the daytime, owls chose areas with closed canopies and increased soil moisture, which likely provided suitable roosting habitat. Owls avoided development but selected areas closer to roads, particularly containing preferred habitats. Understanding of habitat selection across activity periods, temporal windows, and other contexts can improve the conservation of critical habitat for wildlife. Our work contributes to understanding of how animals balance resources related to food provisioning versus safety, both of which are critical for individual fitness and population persistence.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/ornithology/ukaf003","usgsCitation":"Gura, K., Bedrosian, B., Patla, S., and Chalfoun, A.D., 2025, Variation in habitat selection by male Strix nebulosa (Great Gray Owls) across the diel cycle: Ornithology, v. 142, ukaf003, 14 p., https://doi.org/10.1093/ornithology/ukaf003.","productDescription":"ukaf003, 14 p.","ipdsId":"IP-174311","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":489826,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/ornithology/ukaf003","text":"Publisher Index Page"},{"id":489406,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","county":"Teton County","otherGeospatial":"Greater Yellowston Ecosystem","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -111.03645482026093,\n 45.00364303043449\n ],\n [\n -111.03645482026093,\n 43.24877292612567\n ],\n [\n -109.20875713322333,\n 43.24877292612567\n ],\n [\n -109.20875713322333,\n 45.00364303043449\n ],\n [\n -111.03645482026093,\n 45.00364303043449\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"142","noUsgsAuthors":false,"publicationDate":"2025-01-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Gura, Katherine B.","contributorId":356246,"corporation":false,"usgs":false,"family":"Gura","given":"Katherine B.","affiliations":[{"id":36628,"text":"University of Wyoming","active":true,"usgs":false}],"preferred":false,"id":938913,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bedrosian, Bryan","contributorId":199738,"corporation":false,"usgs":false,"family":"Bedrosian","given":"Bryan","affiliations":[{"id":35591,"text":"Teton Raptor Center","active":true,"usgs":false}],"preferred":false,"id":938914,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Patla, Susan","contributorId":356248,"corporation":false,"usgs":false,"family":"Patla","given":"Susan","affiliations":[{"id":36596,"text":"Wyoming Game and Fish Department","active":true,"usgs":false}],"preferred":false,"id":938915,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Chalfoun, Anna D. 0000-0002-0219-6006 achalfoun@usgs.gov","orcid":"https://orcid.org/0000-0002-0219-6006","contributorId":197589,"corporation":false,"usgs":true,"family":"Chalfoun","given":"Anna","email":"achalfoun@usgs.gov","middleInitial":"D.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":938916,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70262231,"text":"sir20245132 - 2025 - Hydrogeologic framework of the Mountain Home area, southern Idaho","interactions":[],"lastModifiedDate":"2025-07-10T15:47:43.187583","indexId":"sir20245132","displayToPublicDate":"2025-01-16T17:28:13","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2024-5132","displayTitle":"Hydrogeologic Framework of the Mountain Home Area, Southern Idaho","title":"Hydrogeologic framework of the Mountain Home area, southern Idaho","docAbstract":"In the arid western Snake River Plain around the City of Mountain Home, Idaho, declining groundwater levels concern agricultural, municipal, and other water users who rely on groundwater for sustenance because surface-water resources are limited. The U.S. Geological Survey developed this hydrogeologic framework to provide an updated characterization of groundwater resources in the western Snake River Plain around the City of Mountain Home. The hydrogeologic framework comprises: (1) a conceptual description of hydrogeologic units, (2) a three-dimensional hydrogeologic model and borehole database, (3) a map of groundwater levels and change, and (4) a discussion of groundwater occurrence and movement within the study area. Hydrogeologic units were defined based on existing literature and the borehole database compiled for this study; the five hydrogeologic units are granite, rhyolite, basalt, fine-grained sediments, and coarse-grained sediments. Each unit can bear water, but the main regional aquifer in the study area occurs in the basalt and fine-grained sediment units with depth to water ranging from 150 to 765 feet. A perched groundwater zone near the City of Mountain Home is primarily hosted in basalt and used domestically with most depths to water ranging from 30 to 100 feet. Interflow zones, scoria, and vertical fractures create heterogeneity within the basalt hydrogeologic unit that exerts strong control on groundwater movement, creating horizontal perching conditions and zones of enhanced vertical conductivity that facilitate downward groundwater percolation. In the fine- and coarse-grained sediments and rhyolite units, inferred faults both impede and enhance groundwater movement. The borehole database was constructed by digitizing 540 well-driller reports and was used to build a three-dimensional hydrogeologic framework model which reasonably represents the spatial distribution of hydrogeologic units in the study area. Generally, fine-grained sediments underlie much of the study area, with basalt concentrated in the central and western study area and rhyolite and granite in the uplands to the north. Groundwater levels were measured in 180 wells in March and November 2023; these data were used to develop water-table contour maps and describe groundwater-level change over an irrigation season. Groundwater generally flows south-southwest to the Snake River and groundwater levels declined across most of the study area (from 0.03 to 22.01 feet) between spring and autumn 2023, which is consistent with long-term declines in the Cinder Cone Butte Critical Groundwater Area and Mountain Home Groundwater Management Area. Groundwater levels rose (0.6 to 15.44 feet) over the irrigation season in most wells in the perched groundwater zone near the City of Mountain Home and near the Snake River, indicating the importance of surface-water recharge to groundwater in areas where surface water irrigation occurs. In aggregate, this hydrogeologic framework provides an updated characterization of and new insights into groundwater resources in the study area to help inform water resources management.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20245132","collaboration":"Prepared in cooperation with the Idaho Department of Water Resources","usgsCitation":"Zinsser, L.M., and Ducar, S.D., 2025, Hydrogeologic framework of the Mountain Home area, southern Idaho: U.S. Geological Survey Scientific Investigations Report 2024–5132, 47 p., https://doi.org/10.3133/sir20245132.","productDescription":"Report: vii, 47 p.; Data Release","numberOfPages":"47","onlineOnly":"Y","ipdsId":"IP-140356","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":492032,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118332.htm","linkFileType":{"id":5,"text":"html"}},{"id":466551,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2024/5132/sir20245132.XML"},{"id":466550,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2024/5132/images"},{"id":466549,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P1HK5XWS","text":"USGS data release","description":"USGS data release","linkHelpText":"Hydrogeologic framework of the Mountain Home area, southern Idaho - three-dimensional hydrogeologic framework model, borehole database, well data, water-level contours and groundwater storage change"},{"id":466548,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20245132/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2024-5132"},{"id":466547,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2024/5132/sir20245132.pdf","text":"Report","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2024-5132"},{"id":466546,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2024/5132/coverthb.jpg"}],"country":"United States","state":"Idaho","otherGeospatial":"Mountain Home area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -116.5,\n 43.5\n ],\n [\n -116.5,\n 42.833\n ],\n [\n -115,\n 42.833\n ],\n [\n -115,\n 43.5\n ],\n [\n -116.5,\n 43.5\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Idaho Water Science Center
U.S. Geological Survey
230 Collins Rd
Boise, Idaho 83702-4250
Geologic, or naturally occurring, hydrogen has the potential to become a new, low-carbon, primary energy resource. Often referred to as “white” or “gold” hydrogen, this gas occurs naturally in the Earth’s subsurface, similar to petroleum resources. However, unlike petroleum, which releases carbon dioxide when burned, burning hydrogen only produces water as a byproduct. Exploration for geologic hydrogen remains in an early stage and discoveries of high concentrations of subsurface hydrogen are still relatively rare. To facilitate research and exploration for this potential resource, this report presents the first publicly available prospectivity map of geologic hydrogen accumulations in the conterminous United States. Prospective regions are those regions in which all major components necessary for a hydrogen accumulation likely are present—a source of sufficient hydrogen generation, porous reservoirs for storage, and seals to prevent leakage. The midcontinent region of the United States and the central California coast are revealed as having high prospectivity. This analysis also identifies previously unrecognized prospective regions that may be favorable due to long distance lateral migration of subsurface hydrogen, such as the offshore eastern seaboard of the United States, and can provide a linkage between surface observations of hydrogen degassing and far-field source regions. The methodology developed to create this map is expandable and flexible and may be adapted to incorporate new concepts in the hydrogen system and for application to other regions of the world.
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U.S. Geological Survey
Box 25046, Mail Stop 939
Denver, CO 80225
Accurate estimation of population parameters for imperiled wildlife is crucial for effective conservation decision-making. Population density is commonly used for monitoring imperiled species across space and time, and spatial capture–recapture (SCR) models can produce unbiased density estimates. However, many imperiled species are restricted to fragmented remnant habitats in landscapes severely modified by humans, which can alter animal space use in ways that violate typical SCR model assumptions, possibly cryptically biasing density estimates and misinforming conservation actions. Using data from a two-year camera-trapping survey in the Central Pacific Coast region, Mexico, we demonstrate the potential importance to endangered jaguar (Panthera onca) conservation of considering non-circular home ranges when estimating population density with SCR. Strong evidence existed that jaguars had elliptical home ranges wherein movements primarily occurred along linearly arranged coastal habitats that the camera array aligned with. Accounting for this movement with the SCR anisotropic detection function transformation, density estimates were 30%–32% higher than estimates from standard SCR models that assumed circular home ranges. Given much of suitable jaguar habitat in Mexico is fragmented and linearly oriented along coastlines and mountain ranges, accommodating irregular space use in SCR may be critical for obtaining reliable density estimates to inform effective jaguar conservation.
","language":"English","publisher":"Society for Conservation Biology","doi":"10.1111/csp2.13301","usgsCitation":"Murphy, S.M., and Luja, V.H., 2025, Jaguar density estimation in Mexico: The conservation importance of considering home range orientation in spatial capture–recapture: Conservation Science and Practice, v. 7, no. 2, e13301, 13 p., https://doi.org/10.1111/csp2.13301.","productDescription":"e13301, 13 p.","ipdsId":"IP-166818","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":487692,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/csp2.13301","text":"Publisher Index Page"},{"id":482508,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Mexico","state":"Nayarit","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -105.20025596676486,\n 21.09494336619629\n ],\n [\n -104.64414024546751,\n 21.131999296986905\n ],\n [\n -104.84275300307384,\n 22.257694993464256\n ],\n [\n -105.46838318953313,\n 22.487273491981583\n ],\n [\n -105.69678786078022,\n 22.377123069346496\n ],\n [\n -105.56768956833629,\n 21.79740977986144\n ],\n [\n -105.2598397940464,\n 21.50204709859902\n ],\n [\n -105.20025596676486,\n 21.09494336619629\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"7","issue":"2","noUsgsAuthors":false,"publicationDate":"2025-01-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Murphy, Sean M. 0000-0002-9404-8878","orcid":"https://orcid.org/0000-0002-9404-8878","contributorId":346967,"corporation":false,"usgs":true,"family":"Murphy","given":"Sean","middleInitial":"M.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":928674,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Luja, Victor H.","contributorId":332955,"corporation":false,"usgs":false,"family":"Luja","given":"Victor","email":"","middleInitial":"H.","affiliations":[{"id":79701,"text":"Coordinación de Investigación y Posgrado, Unidad Académica de Turismo, Universidad Autónoma de Nayarit, Ciudad de la Cultura S/N. C.P., 63000 Tepic, Nayarit, México","active":true,"usgs":false}],"preferred":false,"id":928675,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70262454,"text":"70262454 - 2025 - Tracing metal sources and groundwater flow paths in the Upper Animas River watershed using rare earth elements and stable isotopes","interactions":[],"lastModifiedDate":"2025-02-11T15:45:16.210494","indexId":"70262454","displayToPublicDate":"2025-01-16T10:25:40","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1758,"text":"Geochemistry: Exploration, Environment, Analysis","active":true,"publicationSubtype":{"id":10}},"title":"Tracing metal sources and groundwater flow paths in the Upper Animas River watershed using rare earth elements and stable isotopes","docAbstract":"Groundwater flow paths and processes that govern metal mobility and transport are difficult to characterize in mountainous bedrock watersheds. Despite the difficulty in holistic characterization, conceptual understanding of subsurface hydrologic and geochemical processes is key to developing remediation plans for locations affected by acid mine drainage, such as the Upper Animas River watershed in southwestern Colorado, USA. Stable isotopes of water and rare earth elements were utilized to evaluate groundwater flow and metal sources within this complex catchment. Stable isotope samples collected from draining mine adits and springs display systematic spatial variation wherein sample sites at higher elevations have greater seasonal variability than sites at lower elevations. The Upper Cement Creek watershed, where multiple draining mines are present, displays the lowest seasonal variation in stable isotopic signatures, potentially indicating the presence of a large, well-mixed volume of groundwater storage or interbasin groundwater flow. Rare earth elements display statistically significant variation between different alteration styles in the catchment. Overprinting of regional propylitic alteration is evident based on enrichment of middle rare earth elements in acidic springs and mines that are not spatially associated with surficial exposures of acid generating alteration styles. Europium anomaly and middle rare earth enrichment signatures from two flooded mine tunnels on opposite sides of a watershed divide indicate connections to the same subsurface flooded mine workings.
","language":"English","publisher":"Geological Society of London","doi":"10.1144/geochem2024-023","usgsCitation":"Newman, C.P., Cowie, R.M., Wilkin, R., and Navarre-Sitchler, A., 2025, Tracing metal sources and groundwater flow paths in the Upper Animas River watershed using rare earth elements and stable isotopes: Geochemistry: Exploration, Environment, Analysis, v. 25, no. 1, geochem2024-023, 13 p., https://doi.org/10.1144/geochem2024-023.","productDescription":"geochem2024-023, 13 p.","ipdsId":"IP-165955","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":480747,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":481028,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1144/geochem2024-023","text":"Publisher Index Page"}],"country":"United States","state":"Colorado","otherGeospatial":"Upper Animas River watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -107.70,\n 37.93\n ],\n [\n -107.70,\n 37.86\n ],\n [\n -107.56,\n 37.86\n ],\n [\n -107.56,\n 37.93\n ],\n [\n -107.70,\n 37.93\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"25","issue":"1","noUsgsAuthors":false,"publicationDate":"2025-02-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Newman, Connor P. 0000-0002-6978-3440","orcid":"https://orcid.org/0000-0002-6978-3440","contributorId":222596,"corporation":false,"usgs":true,"family":"Newman","given":"Connor","email":"","middleInitial":"P.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":924248,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cowie, Rory M.","contributorId":270098,"corporation":false,"usgs":false,"family":"Cowie","given":"Rory","email":"","middleInitial":"M.","affiliations":[{"id":56077,"text":"Alpine Water Resources","active":true,"usgs":false}],"preferred":false,"id":924249,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wilkin, Rick 0000-0002-8635-9545","orcid":"https://orcid.org/0000-0002-8635-9545","contributorId":345122,"corporation":false,"usgs":false,"family":"Wilkin","given":"Rick","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":924250,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Navarre-Sitchler, Alexis","contributorId":190441,"corporation":false,"usgs":false,"family":"Navarre-Sitchler","given":"Alexis","email":"","affiliations":[],"preferred":false,"id":924251,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70262495,"text":"70262495 - 2025 - Forecasting water levels using the ConvLSTM algorithm in the Everglades, USA","interactions":[],"lastModifiedDate":"2025-01-17T16:06:37.26906","indexId":"70262495","displayToPublicDate":"2025-01-16T10:01:57","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Forecasting water levels using the ConvLSTM algorithm in the Everglades, USA","docAbstract":"Forecasting water levels in complex ecosystems like wetlands can support effective water resource management, ecological conservation, and understanding surface and groundwater hydrology. Predictive models can be used to simulate the complex interactions among natural processes, hydrometeorological factors, and human activities. The Greater Everglades in the USA is a well-known example of an ecosystem where complexity has motivated adoption of machine learning algorithms in water level prediction studies. This paper aims to contribute to extending existing machine learning algorithms by integrating spatiotemporal data with deep-learning algorithms in the forecasting process. In this study, a deep-learning model is developed to predict water levels on a regional scale, covering a large area of approximately 9,138 square kilometers in the Everglades ecosystem. This model has the architecture of Convolutional Long Short-Term Memory which can deal with spatiotemporal data by capturing both spatial and temporal dependencies in the training data. The forecasting capabilities of this model (referred to as the global model) are assessed by comparing the global model to two Artificial Neural Networks developed at two different gaging stations, referred to here as local models. One local model is developed at a gaging station directly influenced by nearby water control structures, whereas the other is developed at a gaging station located farther away from these structures. By leveraging data from the Everglades Depth Estimation Network spanning from January 2002 to May 2023, the global and local models were trained to forecast water levels with a two-day lead time. Our findings suggest that both the global and local models perform with approximately the same level of accuracy, with Mean Absolute Relative Error values ranging from 0.38% to 1.4% at the selected stations. The developed global model has demonstrated strong potential as a standalone forecasting tool for the entire study area in the Everglades and could eliminate the need for developing multiple local models. This finding also highlights how machine learning can capture complex spatial and temporal relationships to generate accurate water level predictions on a regional scale.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2024.132195","usgsCitation":"Bassah, R., Corzo Perez, G.A., Bhattacharya, B., Haider, S., Swain, E.D., and Aumen, N., 2025, Forecasting water levels using the ConvLSTM algorithm in the Everglades, USA: Journal of Hydrology, v. 652, 132195, 17 p., https://doi.org/10.1016/j.jhydrol.2024.132195.","productDescription":"132195, 17 p.","ipdsId":"IP-165910","costCenters":[{"id":269,"text":"FLWSC-Ft. Lauderdale","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":27821,"text":"Caribbean-Florida Water Science Center","active":true,"usgs":true}],"links":[{"id":489132,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jhydrol.2024.132195","text":"Publisher Index Page"},{"id":480739,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Everglades","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -80.15272667125285,\n 26.85302740104224\n ],\n [\n -81.52356680957865,\n 26.85302740104224\n ],\n [\n -81.52356680957865,\n 25.136407133512265\n ],\n [\n -80.15272667125285,\n 25.136407133512265\n ],\n [\n -80.15272667125285,\n 26.85302740104224\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"652","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Bassah, Raidan","contributorId":349546,"corporation":false,"usgs":false,"family":"Bassah","given":"Raidan","affiliations":[{"id":49677,"text":"IHE Delft Institute for Water Education","active":true,"usgs":false}],"preferred":false,"id":924376,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Corzo Perez, Gerald A.","contributorId":332614,"corporation":false,"usgs":false,"family":"Corzo Perez","given":"Gerald","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":924377,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bhattacharya, Biswa 0000-0002-8046-589X","orcid":"https://orcid.org/0000-0002-8046-589X","contributorId":298961,"corporation":false,"usgs":false,"family":"Bhattacharya","given":"Biswa","email":"","affiliations":[{"id":49677,"text":"IHE Delft Institute for Water Education","active":true,"usgs":false}],"preferred":false,"id":924378,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Haider, Saira M. 0000-0001-9306-3454","orcid":"https://orcid.org/0000-0001-9306-3454","contributorId":206253,"corporation":false,"usgs":true,"family":"Haider","given":"Saira","middleInitial":"M.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":924379,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Swain, Eric D. 0000-0001-7168-708X edswain@usgs.gov","orcid":"https://orcid.org/0000-0001-7168-708X","contributorId":1538,"corporation":false,"usgs":true,"family":"Swain","given":"Eric","email":"edswain@usgs.gov","middleInitial":"D.","affiliations":[{"id":27821,"text":"Caribbean-Florida Water Science Center","active":true,"usgs":true}],"preferred":true,"id":924380,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Aumen, Nicholas 0000-0002-5277-2630","orcid":"https://orcid.org/0000-0002-5277-2630","contributorId":223550,"corporation":false,"usgs":true,"family":"Aumen","given":"Nicholas","affiliations":[{"id":269,"text":"FLWSC-Ft. Lauderdale","active":true,"usgs":true}],"preferred":true,"id":924381,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70262136,"text":"70262136 - 2025 - Optimization of wetland environmental DNA metabarcoding protocols for Great Lakes region herpetofauna","interactions":[],"lastModifiedDate":"2025-01-30T15:42:13.247195","indexId":"70262136","displayToPublicDate":"2025-01-16T09:39:26","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5840,"text":"Environmental DNA","active":true,"publicationSubtype":{"id":10}},"title":"Optimization of wetland environmental DNA metabarcoding protocols for Great Lakes region herpetofauna","docAbstract":"Many species of reptiles and amphibians (herpetofauna) rely on wetlands that are being degraded and lost at a high rate. Characterization of herpetofauna diversity in different wetland types may help guide conservation strategies. However, traditional survey methods often involve sampling within small temporal windows, and the gear deployed may be taxonomically biased, thus, they may fail to accurately characterize species presence/absence and diversity. In contrast, environmental (e)DNA metabarcoding has been shown to effectively survey entire aquatic communities and can provide a useful complement to traditional surveys. The objective of this study was to design and optimize eDNA sampling and laboratory protocols for wetland herpetofauna. Protocols evaluated included different water sampling approaches (point versus transect sampling), seasonality of sampling, and choice of metabarcoding marker (mitochondrial 12S versus 16S rDNA). Samples collected from 10 sites across southern Michigan detected 17 amphibian and five reptile species, including four species of conservation concern (Ambystoma texanum, Clemmys guttata, Rana palustris, and Sternotherus odoratus). We observed no difference in the number of species detected between point and transect samples (p = 0.70), but point sampling required less time (p = 0.03) and allowed significantly larger volumes of water to be filtered (p = 1.13e-5). No difference in species richness was observed between the 12S and 16S mitochondrial DNA markers (p = 0.96). However, a greater number of taxa were identifiable at the species level when using the 16S locus. There was also a significant difference in the number of species detected between early and late summer sampling periods (more species detected in the earlier period; p = 6.31e-6), and some species were only found in the early or late sampling period. Sampling during multiple periods to fully characterize species composition, the use of point sampling, and the 16S mtDNA marker for herpetofauna eDNA metabarcoding studies may increase efficiency and reliability of results.
","language":"English","publisher":"Wiley","doi":"10.1002/edn3.70047","usgsCitation":"Ruppert, O., Homola, J.J., Kanefsky, J., Swinehart, A., Scribner, K., and Robinson, J.D., 2025, Optimization of wetland environmental DNA metabarcoding protocols for Great Lakes region herpetofauna: Environmental DNA, v. 7, no. 1, e70047, 16 p., https://doi.org/10.1002/edn3.70047.","productDescription":"e70047, 16 p.","ipdsId":"IP-166473","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":489854,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/edn3.70047","text":"Publisher Index Page"},{"id":481505,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7","issue":"1","noUsgsAuthors":false,"publicationDate":"2025-01-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Ruppert, Olivia M.","contributorId":348207,"corporation":false,"usgs":false,"family":"Ruppert","given":"Olivia M.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":923245,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Homola, Jared Joseph 0000-0003-3821-7224","orcid":"https://orcid.org/0000-0003-3821-7224","contributorId":303741,"corporation":false,"usgs":true,"family":"Homola","given":"Jared","email":"","middleInitial":"Joseph","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":923246,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kanefsky, Jeannette","contributorId":243198,"corporation":false,"usgs":false,"family":"Kanefsky","given":"Jeannette","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":923247,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Swinehart, Alyssa","contributorId":348208,"corporation":false,"usgs":false,"family":"Swinehart","given":"Alyssa","affiliations":[{"id":15305,"text":"Grand Valley State University","active":true,"usgs":false}],"preferred":false,"id":923248,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Scribner, Kim T.","contributorId":340939,"corporation":false,"usgs":false,"family":"Scribner","given":"Kim T.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":923249,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Robinson, John D.","contributorId":288851,"corporation":false,"usgs":false,"family":"Robinson","given":"John","email":"","middleInitial":"D.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":923250,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70267507,"text":"70267507 - 2025 - Accurate simulation of flow through dipping aquifers with MODFLOW 6 using enhanced cell connectivity","interactions":[],"lastModifiedDate":"2025-05-28T14:18:54.211849","indexId":"70267507","displayToPublicDate":"2025-01-16T09:15:42","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3825,"text":"Groundwater","active":true,"publicationSubtype":{"id":10}},"title":"Accurate simulation of flow through dipping aquifers with MODFLOW 6 using enhanced cell connectivity","docAbstract":"In simulations of groundwater flow through dipping aquifers, layers of model cells are often “deformed” to follow the top and bottom elevations of the aquifers. When this approach is used in MODFLOW, adjacent cells within the same model layer are vertically offset from one another, and the standard conductance-based (two-point) formulation for flow between cells does not rigorously account for these offsets. The XT3D multi-point flow formulation in MODFLOW 6 is designed to account for geometric irregularities in the grid, including vertical offsets, and to provide accurate results for both isotropic and anisotropic groundwater flow. A recent study evaluated the performance of the standard formulation and XT3D using a simple, synthetic benchmark model of a steeply dipping aquifer. Although XT3D generally improved the accuracy of flow simulations relative to the standard formulation as expected, neither formulation produced accurate flows in cases that involved large vertical offsets. In this paper, we explain that the inability of XT3D to produce accurate flows in the steeply dipping aquifer benchmark was not due to an inherent limitation of the flow formulation, but rather to the limited cell connectivity inherent in the most commonly used discretization packages in MODFLOW 6. Furthermore, we demonstrate that XT3D is able to produce the expected accuracy when adequate cell connectivity is introduced using MODFLOW's unstructured grid type and the aquifer is discretized vertically using at least two model layers.
","language":"English","publisher":"National Groundwater Association","doi":"10.1111/gwat.13459","usgsCitation":"Provost, A.M., Bardot, K., Langevin, C.D., and McCallum, J., 2025, Accurate simulation of flow through dipping aquifers with MODFLOW 6 using enhanced cell connectivity: Groundwater, v. 63, no. 3, p. 399-408, https://doi.org/10.1111/gwat.13459.","productDescription":"10 p.","startPage":"399","endPage":"408","ipdsId":"IP-167149","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":488469,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/gwat.13459","text":"Publisher Index Page"},{"id":486638,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"63","issue":"3","noUsgsAuthors":false,"publicationDate":"2025-01-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Provost, Alden M. 0000-0002-4443-1107 aprovost@usgs.gov","orcid":"https://orcid.org/0000-0002-4443-1107","contributorId":2830,"corporation":false,"usgs":true,"family":"Provost","given":"Alden","email":"aprovost@usgs.gov","middleInitial":"M.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":938448,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bardot, Kerry","contributorId":355958,"corporation":false,"usgs":false,"family":"Bardot","given":"Kerry","affiliations":[{"id":84875,"text":"School of Earth Sciences, Univ. of Western Australia","active":true,"usgs":false}],"preferred":false,"id":938449,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Langevin, Christian D. 0000-0001-5610-9759 langevin@usgs.gov","orcid":"https://orcid.org/0000-0001-5610-9759","contributorId":1030,"corporation":false,"usgs":true,"family":"Langevin","given":"Christian","email":"langevin@usgs.gov","middleInitial":"D.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":938450,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McCallum, James L.","contributorId":355959,"corporation":false,"usgs":false,"family":"McCallum","given":"James L.","affiliations":[{"id":84875,"text":"School of Earth Sciences, Univ. of Western Australia","active":true,"usgs":false}],"preferred":false,"id":938451,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70264082,"text":"70264082 - 2025 - Ecohydrological response of a forested headwater catchment to a flash drought in the Southeastern U.S.","interactions":[],"lastModifiedDate":"2025-03-06T15:26:45.148976","indexId":"70264082","displayToPublicDate":"2025-01-16T09:06:34","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Ecohydrological response of a forested headwater catchment to a flash drought in the Southeastern U.S.","docAbstract":"Flash droughts differ from traditionally defined droughts in their rapidity of intensification and often associated high vapor-pressure deficit. These droughts can lead to declines in streamflow and water table depth and induce water stress to vegetation at a greater rate than droughts that manifest over longer periods. However, little is known regarding the response of forested environments to flash drought because most studies of impacts have been conducted in agricultural settings. In this study we investigated water-use patterns of riparian trees using sap flow methods and examined the role of groundwater as a source of moisture over three periods that were delimited by antecedent soil moisture conditions. For a longer-term perspective we also examine monthly streamflow over the 35-year record. We observed that trees at only one monitoring plot showed a decrease in water use relative to evaporative demand during a flash drought. Total reverse sap flow (flow toward the roots rather than the canopy) greatly increased during the flash drought period, suggesting the likely occurrence of hydraulic redistribution to the excessively dry soils. Over the drought period groundwater became a more dominant source of moisture for sustaining forest water use. Monthly mean streamflow during the flash drought approached levels observed in past multiyear droughts. This is the first study, to our knowledge, to specifically investigate the response of multiple water budget components to flash drought in a humid forest. As more studies are conducted, a better understanding of the range of expected responses are likely to emerge.
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Persistent organic pollutants (POPs) have known detrimental effects on human and wildlife health. Ubiquitous in the environment, these degradation-resistant chemicals have a high bioaccumulation potential. This case study describes the interdisciplinary plan and One Health design implemented to measure the role of harmful pollutants in the occurrence of a marine turtle panzootic fibropapillomatosis (FP). FP is a neoplastic disease that causes the growth of debilitating tumours on soft tissues and internal organs. Disease incidence has been increasing significantly throughout the Anthropocene and the reasons are still uncertain. The pervasive effect of pollution in marine coastal habitats has often been hypothesized as a driver of high disease prevalence but never fully tested. Our project combines disease ecology, marine field biology, and chemical toxicology in the attempt to unravel the intricate dynamics behind FP. We here describe the complex process used to develop a methodology to measure levels of harmful seawater pollutants such as polychlorinated biphenyls (PCBs), polycyclic aromatic hydrocarbons (PAHs), and organochlorine pesticides (OCPs) in important sea turtle habitats in Florida. The proposed contaminants are among the top priority harmful pollutants, highly carcinogenic in aquatic animals, and bioaccumulate in sea turtles. Although only providing a description of the methodological process, this case study can help future research to apply similar transdisciplinary studies in the context of wildlife diseases. Understanding the effects of anthropogenic-driven pollution activity on ocean health can clarify its consequences to the health of wildlife and humans living in and around that environment.
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For almost all cyanobacteria, habitat amelioration was necessary for growth in the field. Despite differences in inocula composition following cultivation, restoration outcomes five months after inoculation were poor with no significant increases in cyanobacterial abundance, soil chlorophyll a, or soil exopolysaccharide content. Thus, more work is needed to boost the initial growth and survival of biocrust inocula, regardless of the method of cultivation (i.e., greenhouse or field). Future work focused on assessing opportunities for habitat amelioration during application to improve biocrust establishment during this critical restoration phase would be highly valuable.
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Water Resources Mission Area
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, Virginia 20192
Contact Integrated Water Availability Assessment Team
","tableOfContents":"The steady rise in global temperature as a result of human activity is causing changes in Earth’s water cycle. The balance of water stored within and moving between vapor, liquid, and frozen states in the water cycle is shifting, with consequences for water availability that include increases in drought, fire weather, flooding, and heavy precipitation, as well as cryosphere decline and sea-level rise. In this chapter of the U.S. Geological Survey Integrated Water Availability Assessment—2010–20, we provide an overview of climate-change observations and projections from Earth-system model simulations that relate to future water availability, from global and national climate assessments and from the published literature. Effects of climate change on primary water-cycle components are discussed in context of how global-scale hydroclimate drivers influence regional processes within the United States. Understanding the major climate drivers impacting the water cycle is crucial to predicting future changes in water availability and developing adaptation strategies to ensure human and ecosystem water supplies. First, we provide background information on the water cycle, the climate-model ensemble simulations developed to produce projections based on warming scenarios, and attribution and certainty levels. Tipping points, self-reinforcing feedbacks, cascading effects, and compound extremes are introduced. The framework of climatic impact drivers (CIDs) outlined in the Intergovernmental Panel on Climate Change Sixth Assessment Report (IPCC AR6) is used to show primary drivers of physical change to the water cycle and to understand and predict changes in future water availability. Specific climate-change related observations and projections are discussed for water cycle components of precipitation, evapotranspiration, soil moisture, streamflow, lakes and wetlands, ice and snow, and groundwater, as well as their implications for future water availability for humans and ecosystems. The chapter concludes with a synthesis discussion of three examples of complex regional-scale hydroclimate processes that influence water availability for populations in the United States, including (1) mountain and coastal precipitation, (2) aridification and drought, and (3) the influence of forest-cover change on terrestrial water-vapor recycling.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1894E","programNote":"Water Availability and Use Science Program and National Water Quality Program","usgsCitation":"Scholl, M.A., McCabe, G.J., Olson, C.G., and Powlen, K.A., 2025, Climate change and future water availability in the United States, chap. 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Water Resources Mission Area
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, Virginia 20192
Contact Integrated Water Availability Assessment Team
Withdrawals of water for human use are fundamental to the evaluation of the Nation’s water availability. This chapter provides an analysis of public supply, crop irrigation, and thermoelectric power water use for the conterminous United States (CONUS) during water years 2010–20. These three categories account for about 90 percent of water withdrawals in the Nation. The values presented here are based on modeling approaches that estimate water use at temporal (monthly) and spatial scales (12-digit hydrologic unit code—small watersheds sized 50–100 square kilometers) compatible for integration into a broader national assessment of water availability. Models also provide an understanding of factors that influence water use.
An estimated 244,817 million gallons per day (Mgal/d; 28,677 million cubic meters per month [Mm3/mo]) were withdrawn on average within the CONUS during water years 2010–20 from fresh water and saline water for crop irrigation, public supply, and thermoelectric power, with shares of 43, 14.5, and 42.5 percent for each of these categories, respectively. In the same period, estimated withdrawals and consumptive use (1) for public supply were 35,400 and 4,219 Mgal/d (4,081 and 486 Mm3/mo), respectively; (2) for crop irrigation were 105,497 and 75,698 Mgal/d (12,147 and 8,716 Mm3/mo), respectively; and (3) for thermoelectric power from fresh water were 82,656 and 2,904 Mgal/d (9,952 and 345 Mm3/mo), respectively.
Withdrawals for these categories of water use are highly spatially variable, with western States dominated by crop irrigation and eastern States dominated by thermoelectric-power water use. Public supply accounts for the largest percentage of water use in several heavily populated northeastern States. Reliance on groundwater compared to surface water depends on the availability of water sources and the type of water use. For public supply, withdrawals from groundwater are greater than withdrawals from surface water in the Western aggregated hydrologic regions, whereas the balance shifts to more surface water for the rest of the CONUS. In all aggregated hydrologic regions, the predominant source of water for crop irrigation is groundwater. Most thermoelectric power facilities in the eastern half of the CONUS use surface water from freshwater and saline sources; most thermoelectric power facilities in the western half of the CONUS use groundwater.
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D of U.S. Geological Survey Integrated Water Availability Assessment—2010–20: U.S. Geological Survey Professional Paper 1894–D, 56 p., https://doi.org/10.3133/pp1894D.","productDescription":"ix, 56 p.","numberOfPages":"72","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-158787","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":466179,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/pp/1894/d/pp1894D.pdf","text":"Report","size":"42.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"PP 1894–D"},{"id":466178,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/pp/1894/d/coverthb.jpg"},{"id":481885,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/pp/1894/d/pp1894D.XML","linkFileType":{"id":8,"text":"xml"}},{"id":481906,"rank":5,"type":{"id":39,"text":"HTML 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Water Resources Mission Area
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, Virginia 20192
Contact Integrated Water Availability Assessment Team
","tableOfContents":"Degradation of water quality can make water harmful or unusable for humans and ecosystems. Although many studies have assessed the effect of individual constituents or narrow suites of constituents on freshwater systems, no consistent, comprehensive assessment exists over the wide range of water-quality effects on water availability. Using published studies, data, and models completed at regional or national scales in the United States during 2010–20, this chapter moves towards a comprehensive assessment by summarizing how selected anthropogenic and geogenic water-quality constituents affect national-scale water availability for human and ecosystem needs. Several types of human health, agricultural, ecological, and beneficial-use standards or thresholds were used to provide context for categorizing surface-water and groundwater quality.
Water availability for human and ecological use is limited by elevated concentrations of geogenic and anthropogenic constituents in surface and groundwater. Elevated concentrations of five geogenic constituents (arsenic, manganese, strontium, radium, and adjusted gross alpha) are common in groundwater and collectively affect the drinking water supply to over 30 million people. Surface water sourced drinking water supplies are impaired in about a third of assessed stream miles, most commonly because of non-mercury metals and salinity. Health-based violations at community water systems may disproportionately affect socially vulnerable communities. Ecological water uses are predominantly limited by nutrients, sediment, temperature, pathogens, salinity, and pesticides.
Water availability for human and ecological use is adversely affected by human activities including human contaminant sources (for example, wastewater, agriculture), processes (for example, dredging, groundwater pumping), or permanent landscape modifications (for example, dams, urbanization). Primary contaminant sources vary spatially and include fertilizer and manure, atmospheric deposition, wastewater treatment plants, urban land, and a range of natural sources. Contaminants of emerging concern, contaminants without regulatory thresholds, and mixtures of geogenic and anthropogenic water contaminants also contribute to ecological degradation and human exposure.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1894C","programNote":"Water Availability and Use Science Program and National Water Quality Program","usgsCitation":"Erickson, M.L., Miller, O.L., Cashman, M.J., Degnan, J.R., Reddy, J.E., Martinez, A.J., and Azadpour, E., 2025, Status of water-quality conditions in the United States, 2010–20 (ver. 1.1, February 2025), chap. 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February 5, 2025","contact":"Integrated Water Availability Assessment
Water Resources Mission Area
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, Virginia 20192
Contact Integrated Water Availability Assessment Team
","tableOfContents":"We present an assessment of water supply across the conterminous United States (CONUS), Alaska, Hawaii, and Puerto Rico covering water years 2010–20. Our analysis drew on two national hydrologic models, the National Hydrologic Model Precipitation-Runoff Modeling System and the Weather Research and Forecasting model hydrologic modeling system. Both models produced estimates of streamflow, evapotranspiration, soil moisture, snow water equivalent, and other hydrologic states and fluxes. The models were driven by the bias-adjusted 4-kilometer-resolution, long-term regional hydroclimate simulation over the conterminous United States dataset (CONUS404). We assessed spatial and temporal error distributions by comparing monthly simulations at the 12-digit hydrologic unit code and regional scale from both models against external benchmarking datasets. Results showed that average annual rainfall across the CONUS was 857 millimeters per year for the period of analysis, with water year 2012 the driest year (729 millimeters) and water year 2019 the wettest year (995 millimeters). Key interannual variability results included the following: (1) the California–Nevada hydrologic region had the highest variability in precipitation and snow accumulation, and (2) the Texas hydrologic region was among hydrologic regions with the highest variability in precipitation. We related interannual variability in precipitation to storage volumes in soil moisture, snow water equivalent, and lakes and reservoirs to highlight areas with little storage and large year-to-year variability in precipitation. These areas included the Southern High Plains, Central High Plains, Texas, Souris–Red–Rainy, Mississippi Embayment, and Midwest regions. Our analysis of groundwater-level data showed that several of these areas overlap aquifers where groundwater levels were considerably lower than historical averages, including the Colorado Plateaus aquifers, the Rio Grande aquifer system, and the Central and Southern regions of the High Plains aquifer. Many of these lowered groundwater levels are continuations of decades-long declines from overpumping that started well before the assessment period. The resulting water budgets and their analyses provide a high-resolution foundational assessment of the mean state and variability of the terrestrial hydrologic cycle across the CONUS and Alaska, Hawaii, and Puerto Rico to support a wide range of water resource management applications.
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Water Resources Mission Area
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, Virginia 20192
Contact Integrated Water Availability Assessment Team
","tableOfContents":"Water availability is fundamentally important to human well-being, economic vitality, and ecosystem health. Because of its central importance, the U.S. Congress tasked the U.S. Geological Survey (USGS) and other Federal agencies with conducting regular, comprehensive assessments of water availability in the United States through the requirements under the SECURE Water Act. In response to this mandate, the USGS has developed the U.S. Geological Survey Integrated Water Availability Assessment—2010–20, which addresses aspects of water supply, quality, and use related to water availability in the United States. This is the first chapter of that report. The major climatic factors affecting water availability are also described. Multiple aspects of water availability are integrated to produce a more comprehensive analysis of water availability in the United States. This chapter enumerates the development, organization, and tools used in the USGS Integrated Water Availability Assessment. SECURE Water Act reports, developed by the Department of Energy Hydropower Climate Change Assessment and the Bureau of Reclamation West-Wide Climate and Hydrology Assessment, are also described. A distilled list of key findings from the overall report is also provided, serving as an introduction to each topic along with the most important high-level information.
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12201 Sunrise Valley Drive
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Contact Integrated Water Availability Assessment Team
","tableOfContents":"This professional paper is a multichapter report that assesses water availability in the United States for water years 2010–20. This work was conducted as part of the fulfillment of the mandates of Subtitle F of the Omnibus Public Land Management Act of 2009 (Public Law 111-11), also known as the SECURE Water Act. As such, this work examines the spatial and temporal distribution of water quantity and quality in surface water and groundwater, as related to human and ecosystem needs and as affected by human and natural influences. Chapter A introduces the National Integrated Water Availability Assessment and provides important background and definitions for how the report characterizes water availability and its components. Chapter A also presents the key findings of Chapters B–F and thus acts as a summary of the entire report. Chapter B is a national assessment of water supply, which is the quantity of water supplied through climatic inputs. Chapter C is a national assessment of water quality, which is the chemical and physical characteristics of water. Chapter D assesses water use including withdrawals and consumptive use in the conterminous United States. Chapter E presents an analysis of factors affecting future water availability under changing climate conditions. The National Integrated Water Availability Assessment culminates with Chapter F, which is an integrated assessment of water availability that considers the amount and quality of water coupled with the suitability of that water for specific uses. Together, these six chapters constitute the National Integrated Water Availability Assessment for water years 2010–20.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1894","usgsCitation":"Stets, E.G., ed., 2025, U.S. Geological Survey Integrated Water Availability Assessment—2010–20: U.S. Geological Survey Professional Paper 1894, [variously paged], https://doi.org/10.3133/pp1894.","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":466164,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/pp/1894/coverthb.jpg"},{"id":467974,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/pp/1894/a/pp1894A.pdf","text":"Report","size":"22.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"PP 1894–A"}],"contact":"Integrated Water Availability Assessment
Water Resources Mission Area
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, Virginia 20192
Contact Integrated Water Availability Assessment Team
","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2025-01-15","noUsgsAuthors":false,"publicationDate":"2025-01-15","publicationStatus":"PW","contributors":{"editors":[{"text":"Stets, Edward G. 0000-0001-5375-0196 estets@usgs.gov","orcid":"https://orcid.org/0000-0001-5375-0196","contributorId":194490,"corporation":false,"usgs":true,"family":"Stets","given":"Edward","email":"estets@usgs.gov","middleInitial":"G.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":923073,"contributorType":{"id":2,"text":"Editors"},"rank":1}]}} ,{"id":70262132,"text":"sim3508 - 2025 - Surficial geology and Quaternary tectonics of the Madison Valley and fault zone, Madison, Gallatin, and Beaverhead Counties, southwest Montana","interactions":[],"lastModifiedDate":"2025-07-10T15:40:13.582709","indexId":"sim3508","displayToPublicDate":"2025-01-15T12:20:00","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3508","displayTitle":"Surficial Geologic Map and Quaternary Tectonics of the Madison Valley and Fault Zone, Madison, Gallatin, and Beaverhead Counties, Southwest Montana","title":"Surficial geology and Quaternary tectonics of the Madison Valley and fault zone, Madison, Gallatin, and Beaverhead Counties, southwest Montana","docAbstract":"The north-northwest-striking Madison fault is approximately 95 kilometers in length, lying at the confluence of the northeastern Basin and Range province and the Yellowstone tectonic parabola. The fault zone consists primarily of west-dipping normal faults that have east-dipping antithetic faults, which create the Madison Valley graben and several northeast-trending intrabasin faults. The Madison fault and associated sections discussed herein refer to the main west-dipping, range-bounding fault along the eastern side of the valley. Detailed geologic mapping (1:12,000 scale) of the entire fault zone and fault scarp profiling (total of 102 profiles) of the Madison fault reveal greater late Quaternary paleoseismic activity towards the south, including at least three paleoevents along the southern part of the fault that postdate Pinedale glaciation. Early to middle Holocene alluvial fans have vertical surface offsets that average between 2.0 and 3.0 meters and define the characteristic single-event surface offset. Pinedale lateral moraines have vertical surface offsets as great as 12.0 meters. Late Pleistocene to Holocene multiple-event fault scarps show little evidence of beveling, suggesting short seismic recurrence intervals and potential late Pleistocene and Holocene temporal clustering. Long-term average tectonic activity rates indicate slip rates ranging from 0.18–0.6 millimeters per year. Based on a comparison of fault-scarp height versus maximum slope angle of known regression lines developed from other paleoseismic investigations, the most recent event ranges from 5–1 ka.
The northern section of the fault zone is defined by multiple normal faults, which detached the hanging walls of Laramide thrust faults within the Paleozoic and Mesozoic strata. This resulted in the partitioning of extension along multiple preexisting structures and less displacement along individual normal fault strands. Structural controls on lateral propagation of individual paleoevents involve the position of lateral ramps along preexisting Laramide contractional faults. This resulted in greater displacement within the larger basement-cored structures along the southern section of the fault zone, where extension is accommodated by one inferred principal basement-involved normal fault. Inferred east-northeast trending, intrabasin, normal faults within the southern half of the fault zone have no late Pleistocene displacement.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/sim3508","programNote":"National Cooperative Geologic Mapping Program","usgsCitation":"Ruleman, C.A., and Brandt, T.R., 2025, Surficial geology and Quaternary tectonics of the Madison Valley and fault zone, Madison, Gallatin, and Beaverhead Counties, southwest Montana: U.S. Geological Survey Scientific Investigations Map 3508, 1 sheet, scale 1:50,000, 45-p. pamphlet, https://doi.org/10.3133/sim3508.","productDescription":"Report: viii, 43 p.; 2 Sheets: 31.40 x 70.84 inches ; Data Release","onlineOnly":"Y","ipdsId":"IP-041748","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":492022,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118303.htm","linkFileType":{"id":5,"text":"html"}},{"id":466446,"rank":7,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sim/3508/sim3508.xml"},{"id":466445,"rank":6,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sim/3508/images"},{"id":466343,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9EENEI7","text":"USGS data release","linkHelpText":"Data Release for Surficial Geology and Quaternary Tectonics of the Madison Valley and Fault Zone, Madison, Gallatin, and Beaverhead Counties, southwest Montana"},{"id":466325,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3508/coverthb.jpg"},{"id":466326,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3508/sim3508_pamphlet.pdf","text":"Pamphlet","size":"78.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3508 pamphlet"},{"id":466341,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3508/sim3508_sheet1.pdf","text":"Sheet 1—Geologic map","size":"45.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3508 sheet 1"},{"id":466342,"rank":4,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3508/sim3508_sheet1_geospatial.pdf","text":"Sheet 1— Georeferenced geologic map","size":"46.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3508 sheet 1 geospatial"}],"country":"United States","state":"Idaho, Montana, Wyoming","county":"Beaverhead County, Gallatin County, Madison County","otherGeospatial":"Madison Valley and fault zone","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -112,\n 45.75\n ],\n [\n -112,\n 43.25\n ],\n [\n -110,\n 43.25\n ],\n [\n -110,\n 45.75\n ],\n [\n -112,\n 45.75\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Geosciences and Environmental Change Science Center
U.S. Geological Survey
Box 25046, MS-980
Denver, CO 80225-0046
The Center for the Advancement of Population Assessment Methodology (CAPAM) was established in 2013, envisioned as an institute that could conduct, organize, and communicate stock assessment research with the aim of benefiting fisheries assessment efforts internationally. CAPAM’s activities have focused on its workshop series and consequent special issues in Fisheries Research. The information generated through CAPAM and its permanent recording as journal articles has greatly benefited the stock assessment community and can potentially contribute to modelling in general. We discuss what has made CAPAM successful, its future, and what could be done to reach the ultimate goal of producing a good practices guide for fisheries stock assessment.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.fishres.2024.107162","usgsCitation":"Maunder, M., Crone, P., Semmens, B.X., Valero, J., Waterhouse, L., Methot, R., and Punt, A.E., 2025, The Center for the Advancement of Population Assessment Methodology (CAPAM): A perspective on the first 10 years: Fisheries Research, v. 281, 107162, 8 p., https://doi.org/10.1016/j.fishres.2024.107162.","productDescription":"107162, 8 p.","ipdsId":"IP-164132","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":466437,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"281","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Maunder, Mark N.","contributorId":348521,"corporation":false,"usgs":false,"family":"Maunder","given":"Mark N.","affiliations":[{"id":83372,"text":"American Tropical Tuna Commission","active":true,"usgs":false}],"preferred":false,"id":923510,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Crone, Paul R.","contributorId":348522,"corporation":false,"usgs":false,"family":"Crone","given":"Paul R.","affiliations":[{"id":18933,"text":"NOAA Southwest Fisheries Science Center","active":true,"usgs":false}],"preferred":false,"id":923511,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Semmens, Brice X.","contributorId":149775,"corporation":false,"usgs":false,"family":"Semmens","given":"Brice","email":"","middleInitial":"X.","affiliations":[{"id":17820,"text":"Scripps Institution of Oceanography, University of California, San Diego","active":true,"usgs":false}],"preferred":false,"id":923512,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Valero, Juan L.","contributorId":348523,"corporation":false,"usgs":false,"family":"Valero","given":"Juan L.","affiliations":[{"id":83375,"text":"Inter-American Tropical Tuna Commission","active":true,"usgs":false}],"preferred":false,"id":923513,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Waterhouse, Lynn 0000-0002-7455-7632","orcid":"https://orcid.org/0000-0002-7455-7632","contributorId":348524,"corporation":false,"usgs":true,"family":"Waterhouse","given":"Lynn","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":923514,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Methot, Richard D.","contributorId":348525,"corporation":false,"usgs":false,"family":"Methot","given":"Richard D.","affiliations":[{"id":83376,"text":"National Marine Fisheries Service – NWFSC","active":true,"usgs":false}],"preferred":false,"id":923515,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Punt, Andre E.","contributorId":172069,"corporation":false,"usgs":false,"family":"Punt","given":"Andre","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":923516,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70262135,"text":"70262135 - 2025 - Endemic and invasive species: A history of distributional trends in the fish fauna of the lower New River drainage","interactions":[],"lastModifiedDate":"2025-01-15T17:02:19.54134","indexId":"70262135","displayToPublicDate":"2025-01-15T09:54:04","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3709,"text":"Water","active":true,"publicationSubtype":{"id":10}},"title":"Endemic and invasive species: A history of distributional trends in the fish fauna of the lower New River drainage","docAbstract":"Invasive species are often central to conservation efforts, particularly when concerns involve potential impacts on rare, endemic native species. The lower New River drainage of the eastern United States is a watershed that warrants conservation assessment, as the system is naturally depauperate of native fish species and it is nearly saturated with non-native fish species: there are 31 natives, including at least nine endemic taxa, and 63 non-natives. For endemic taxa, we examined temporal distribution shifts (range expansions or contractions) based on percent change in the occupied watershed area. We contrasted these findings with time series analyses on distribution trends of non-native minnows (Leuciscidae) and darters (Percidae) based on growth curve models of the cumulative sum of the total area of occupied 12-digit hydrologic unit codes. We documented range reductions for six of nine endemic taxa. We determined that 11 of 18 non-native minnows and 6 of 8 non-native darters were invasive based on range expansions and associated invasion curve models. The endemic taxa are of conservation concern given the limited distribution ranges and documented population declines. Although among-species comparisons of range shifts do not support causal inference, documentation of changes in distribution ranges of endemic and invasive species is critical to inform conservation efforts.
","language":"English","publisher":"MDPI","doi":"10.3390/w17020221","usgsCitation":"Welsh, S.A., Cincotta, D., Owens, N., and Stauffer, J.R., 2025, Endemic and invasive species: A history of distributional trends in the fish fauna of the lower New River drainage: Water, v. 17, no. 2, 221, 23 p., https://doi.org/10.3390/w17020221.","productDescription":"221, 23 p.","ipdsId":"IP-173053","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":466652,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/w17020221","text":"Publisher Index Page"},{"id":466432,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Carolina, Tennessee, Virginia, West Virginia","otherGeospatial":"New River drainage","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -82.06585576020927,\n 38.59746796567387\n ],\n [\n -82.06585576020927,\n 35.986473012540856\n ],\n [\n -80.05188055833794,\n 35.986473012540856\n ],\n [\n -80.05188055833794,\n 38.59746796567387\n ],\n [\n -82.06585576020927,\n 38.59746796567387\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"17","issue":"2","noUsgsAuthors":false,"publicationDate":"2025-01-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Welsh, Stuart A. 0000-0003-0362-054X","orcid":"https://orcid.org/0000-0003-0362-054X","contributorId":217037,"corporation":false,"usgs":true,"family":"Welsh","given":"Stuart","email":"","middleInitial":"A.","affiliations":[{"id":642,"text":"West Virginia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":923241,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cincotta, Daniel A.","contributorId":273118,"corporation":false,"usgs":false,"family":"Cincotta","given":"Daniel A.","affiliations":[{"id":56173,"text":"West Virginia DNR","active":true,"usgs":false}],"preferred":false,"id":923242,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Owens, Nathaniel V.","contributorId":348205,"corporation":false,"usgs":false,"family":"Owens","given":"Nathaniel V.","affiliations":[{"id":6738,"text":"The Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":923243,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stauffer, Jay R. Jr.","contributorId":119700,"corporation":false,"usgs":false,"family":"Stauffer","given":"Jay","suffix":"Jr.","email":"","middleInitial":"R.","affiliations":[{"id":7260,"text":"Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":923244,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70266165,"text":"70266165 - 2025 - Emotions and political identity predict public acceptance of urban deer management","interactions":[],"lastModifiedDate":"2025-04-29T15:10:33.570193","indexId":"70266165","displayToPublicDate":"2025-01-15T09:45:56","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3669,"text":"Urban Ecosystems","active":true,"publicationSubtype":{"id":10}},"title":"Emotions and political identity predict public acceptance of urban deer management","docAbstract":"Addressing public preferences can enhance wildlife management effectiveness and reduce backlash. We conducted novel research on public acceptance of wildlife management by accounting for the role of underexplored drivers including emotion and political identity across an urban-to-rural gradient. Using data from a 2022 survey about white-tailed deer (Odocoileus virginianus) in Durham County, North Carolina, we analyzed drivers of acceptance for three management strategies: passive management, lethal management by hunting, and lethal management by professionals. Support for deer management varied across the urban-to-rural gradient, as rural residents favored hunting but were less supportive of passive management compared to urban and suburban residents. Emotions and general attitudes toward deer were the strongest predictors of management acceptance. Support for passive management was higher among residents with more positive emotions toward deer, whereas support for lethal strategies was higher among those with more negative emotions. Additionally, political identity emerged as a complex yet influential factor in shaping support for lethal management. Conservative respondents exhibited a higher acceptance of hunting, whereas liberal respondents exhibited a higher acceptance of professional sharpshooting. Collectively, our results demonstrate the ways in which emotions, politics, and other socio-demographic factors interact to influence public support for deer management across the urban–rural gradient. When direct experience with wildlife is lacking (e.g., in urban areas), emotions may act as heuristic guides that shape preferences. Managers aiming to increase deer management acceptability could integrate insights about emotional, political, and demographic drivers of public management support in communication efforts, potentially rendering urban deer management more effective.
","language":"English","publisher":"Springer","doi":"10.1007/s11252-024-01667-2","usgsCitation":"Desrochers, H., Peterson, M., Larson, L., Moorman, C.E., Kierepka, E., Kilgo, J.C., and Hostetter, N.J., 2025, Emotions and political identity predict public acceptance of urban deer management: Urban Ecosystems, v. 28, 15, 16 p., https://doi.org/10.1007/s11252-024-01667-2.","productDescription":"15, 16 p.","ipdsId":"IP-169143","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":487840,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s11252-024-01667-2","text":"Publisher Index Page"},{"id":485137,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Carolina","county":"Durham County","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-78.8019,36.2361],[-78.8059,36.0928],[-78.8059,36.0878],[-78.7986,36.085],[-78.7957,36.0858],[-78.7923,36.0854],[-78.7919,36.0772],[-78.7879,36.0758],[-78.7852,36.0703],[-78.7749,36.0707],[-78.7498,36.0718],[-78.7564,36.0532],[-78.7519,36.0491],[-78.7503,36.0468],[-78.7492,36.0427],[-78.747,36.0395],[-78.7499,36.035],[-78.7511,36.0323],[-78.7545,36.0301],[-78.7551,36.0283],[-78.75,36.026],[-78.7422,36.0209],[-78.7353,36.0199],[-78.7324,36.0267],[-78.7278,36.0289],[-78.7272,36.0334],[-78.726,36.0343],[-78.7232,36.0334],[-78.7164,36.0283],[-78.713,36.0278],[-78.7102,36.0287],[-78.7085,36.0287],[-78.7052,36.0223],[-78.7076,36.0132],[-78.7077,36.0087],[-78.7048,36.0091],[-78.6985,36.0131],[-78.7009,36.0068],[-78.714,35.9729],[-78.7372,35.941],[-78.751,35.9307],[-78.7609,35.9176],[-78.8056,35.9281],[-78.8298,35.8689],[-78.89,35.8676],[-78.9076,35.8678],[-78.9144,35.8674],[-78.9332,35.8667],[-78.9587,35.866],[-78.986,35.8644],[-78.9985,35.8641],[-79.011,35.8633],[-79.0161,35.8633],[-79.0142,35.8755],[-79.0124,35.886],[-78.9507,36.2393],[-78.8019,36.2361]]]},\"properties\":{\"name\":\"Durham\",\"state\":\"NC\"}}]}","volume":"28","noUsgsAuthors":false,"publicationDate":"2025-01-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Desrochers, Hannah M.","contributorId":353930,"corporation":false,"usgs":false,"family":"Desrochers","given":"Hannah M.","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":934773,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Peterson, M. Nils","contributorId":353931,"corporation":false,"usgs":false,"family":"Peterson","given":"M. Nils","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":934774,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Larson, Lincoln R.","contributorId":353934,"corporation":false,"usgs":false,"family":"Larson","given":"Lincoln R.","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":934775,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Moorman, Christopher E.","contributorId":140839,"corporation":false,"usgs":false,"family":"Moorman","given":"Christopher","email":"","middleInitial":"E.","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":934776,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kierepka, Elizabeth M.","contributorId":353937,"corporation":false,"usgs":false,"family":"Kierepka","given":"Elizabeth M.","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":934777,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kilgo, John C.","contributorId":221258,"corporation":false,"usgs":false,"family":"Kilgo","given":"John","email":"","middleInitial":"C.","affiliations":[{"id":25513,"text":"USDA Forest Service Southern Research Station","active":true,"usgs":false}],"preferred":false,"id":934778,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hostetter, Nathan J. 0000-0001-6075-2157 nhostetter@usgs.gov","orcid":"https://orcid.org/0000-0001-6075-2157","contributorId":198843,"corporation":false,"usgs":true,"family":"Hostetter","given":"Nathan","email":"nhostetter@usgs.gov","middleInitial":"J.","affiliations":[],"preferred":true,"id":934779,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ]}