{"pageNumber":"54","pageRowStart":"1325","pageSize":"25","recordCount":40764,"records":[{"id":70260964,"text":"70260964 - 2024 - Depths in a day - A new era of rapid-response Raman-based barometry using fluid inclusions","interactions":[],"lastModifiedDate":"2024-12-10T15:38:41.563856","indexId":"70260964","displayToPublicDate":"2024-11-07T09:57:46","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2420,"text":"Journal of Petrology","active":true,"publicationSubtype":{"id":10}},"title":"Depths in a day - A new era of rapid-response Raman-based barometry using fluid inclusions","docAbstract":"<p>Rapid-response petrological monitoring is a major advance for volcano observatories, allowing them to build and validate models of plumbing systems that supply eruptions in near-real-time. The depth of magma storage has recently been identified as high-priority information for volcanic observatories, yet this information is not currently obtainable via petrological monitoring methods on timescales relevant to eruption response. Fluid inclusion barometry (using micro-thermometry or Raman spectroscopy) is a well-established petrological method to estimate magma storage depths and has been proposed to have potential as a rapid-response monitoring tool, although this has not been formally demonstrated. To address this deficiency, we performed a near-real-time rapid-response simulation for the September 2023 eruption of Kīlauea, Hawaiʻi. We show that Raman-based fluid inclusion barometry can robustly determine reservoir depths within a day of receiving samples — a transformative timescale that has not previously been achieved by petrological methods. Fluid inclusion barometry using micro-thermometric techniques has typically been limited to systems with relatively deep magma storage (&gt;0.4 g/cm<sup>3</sup> or &gt;7 km) where measurements of CO<sub>2</sub> density are easy and accurate because the CO<sub>2</sub> fluid homogenizes into the liquid phase. Improvements of the accuracy of Raman spectroscopy measurements of fluids with low CO<sub>2</sub> density over the past couple of decades has enabled measurements of fluid inclusions from shallower magmatic systems. However, one caveat of examining shallower systems is that the fraction of H<sub>2</sub>O in the fluid may be too high to reliably convert CO<sub>2</sub> density to pressure. To test the global applicability of rapid response fluid inclusion barometry, we compiled a global melt inclusion dataset (&gt;4000 samples) and calculate the fluid composition at the point of vapor saturation (⁠X<sub><sup>H</sup>2<sup>O⁠</sup></sub>). We show that fluid inclusions in crystal-hosts from mafic compositions (&lt;57 wt. % SiO<sub>2</sub>) — likely representative of magmas recharging many volcanic systems worldwide — trap fluids with X<sub><sup>H</sup>2<sup>O</sup></sub>&nbsp;low enough to make fluid inclusion barometry useful at many of the world’s most active and hazardous mafic volcanic systems (e.g., Iceland, Hawaiʻi, Galápagos Islands, East African Rift, Réunion, Canary Islands, Azores, Cabo Verde).</p>","language":"English","publisher":"Oxford Academic","doi":"10.1093/petrology/egae119","usgsCitation":"DeVitre, C., Wieser, P.E., Bearden, A.T., Richie, A., Rangel, B., Gleeson, M., Grimsich, J., Lynn, K.J., Downs, D.T., Deligne, N.I., and Mulliken, K.M., 2024, Depths in a day - A new era of rapid-response Raman-based barometry using fluid inclusions: Journal of Petrology, v. 65, no. 11, egae119, 15 p., https://doi.org/10.1093/petrology/egae119.","productDescription":"egae119, 15 p.","ipdsId":"IP-158109","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":466776,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/petrology/egae119","text":"Publisher Index Page"},{"id":464235,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Kilauea","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -155.2575579892722,\n              19.41802727097236\n            ],\n            [\n              -155.2575579892722,\n              19.40813592330987\n            ],\n            [\n              -155.2414055520364,\n              19.40813592330987\n            ],\n            [\n           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0000-0001-7886-4376","orcid":"https://orcid.org/0000-0001-7886-4376","contributorId":290327,"corporation":false,"usgs":true,"family":"Lynn","given":"Kendra","email":"","middleInitial":"J.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":918720,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Downs, Drew T. 0000-0002-9056-1404 ddowns@usgs.gov","orcid":"https://orcid.org/0000-0002-9056-1404","contributorId":173516,"corporation":false,"usgs":true,"family":"Downs","given":"Drew","email":"ddowns@usgs.gov","middleInitial":"T.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":918721,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Deligne, Natalia I. 0000-0001-9221-8581","orcid":"https://orcid.org/0000-0001-9221-8581","contributorId":257389,"corporation":false,"usgs":true,"family":"Deligne","given":"Natalia","email":"","middleInitial":"I.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":918722,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Mulliken, Katherine M. 0000-0003-4190-5060","orcid":"https://orcid.org/0000-0003-4190-5060","contributorId":217810,"corporation":false,"usgs":false,"family":"Mulliken","given":"Katherine","email":"","middleInitial":"M.","affiliations":[{"id":16126,"text":"Alaska Division of Geological and Geophysical Surveys","active":true,"usgs":false}],"preferred":false,"id":918723,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}}
,{"id":70260413,"text":"sir20245035 - 2024 - Potential corrosivity of untreated groundwater in Louisiana","interactions":[],"lastModifiedDate":"2025-12-22T21:37:33.869696","indexId":"sir20245035","displayToPublicDate":"2024-11-06T10:30:11","publicationYear":"2024","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":"2024-5035","displayTitle":"Potential Corrosivity of Untreated Groundwater in Louisiana","title":"Potential corrosivity of untreated groundwater in Louisiana","docAbstract":"<p>Corrosive groundwater can cause lead, copper, and other metals to leach from pipes and plumbing fixtures in water distribution systems. Metals, if ingested, could lead to serious health implications to the nearly 2.9 million people in Louisiana who obtain their drinking water from groundwater sources. Four indices—the Langelier Saturation Index (LSI), Ryznar Stability Index (RSI), Puckorius Scaling Index (PSI), and the Potential to Promote Galvanic Corrosion (PPGC)—in addition to an analysis which normalized the results from the existing indices, the Combined Index (CI), were used to assess the corrosivity of groundwater in Louisiana and identify areas within eight major aquifers and aquifer systems with moderate to high corrosivity potential. The purpose of this study is to provide State and local governments, public water system managers, and the nearly 500,000 private well owners in Louisiana with information needed to manage drinking-water supplies and mitigate potential health risks related to leaching of metals from water pipes and fixtures.</p><p>The average scores of untreated groundwater samples from approximately 375 wells by index are as follows: LSI, −1.28; RSI, 9.78; PSI, 9.34; and CI, 4.14. The PPGC does not produce a numerical score, but the total percentage of class counts can be used to assign a classification; overall, samples in Louisiana were classified as significant concern. The percentages of groundwater samples from wells classified as potentially corrosive, by index, are as follows: LSI, 53&nbsp;percent; RSI, 94 percent; PSI, 81 percent; PPGC, 98 percent; and CI, 81 percent. The percentages of samples classified as indeterminate, by index, are as follows: LSI, 46 percent; RSI, 5&nbsp;percent; PSI, 12 percent; PPGC, 0 percent; and CI, 18&nbsp;percent.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20245035","issn":"2328-0328","collaboration":"Prepared in cooperation with the Louisiana Department of Transportation and Development","usgsCitation":"Robinson, A.L., 2024, Potential corrosivity of untreated groundwater in Louisiana: U.S. Geological Survey Scientific Investigations Report 2024–5035, 52 p., https://doi.org/10.3133/sir20245035.","productDescription":"Report: viii, 52 p.; Appendix; 2 Data Releases","numberOfPages":"64","onlineOnly":"Y","ipdsId":"IP-116152","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":497923,"rank":8,"type":{"id":36,"text":"NGMDB Index 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"nation\":\"USA  \"}}]}","contact":"<p>Director, <a data-mce-href=\"https://www.usgs.gov/centers/lmg-water/\" href=\"https://www.usgs.gov/centers/lmg-water/\">Lower Mississippi-Gulf Water Science Center</a><br>U.S. Geological Survey<br>640 Grassmere Park, Suite 100<br>Nashville, TN 37211<br></p><p><a id=\"LPlnkOWA15180ebd-b368-51d6-d4d0-3194b6e2a465\" class=\"OWAAutoLink\" title=\"https://pubs.usgs.gov/contact\" href=\"https://pubs.usgs.gov/contact\" data-auth=\"NotApplicable\" data-olk-copy-source=\"MailCompose\" data-mce-href=\"../contact\">Contact Us- USGS Publications Warehouse</a></p>","tableOfContents":"<ul><li>Abstract</li><li>Introduction</li><li>Methods Used in the Assessment</li><li>Results and Discussion</li><li>Summary and Conclusions</li><li>Acknowledgments</li><li>References Cited</li><li>Appendix 1. Other Indices</li></ul>","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"publishedDate":"2024-11-06","noUsgsAuthors":false,"plainLanguageSummary":"<p><br data-mce-bogus=\"1\"></p>","publicationDate":"2024-11-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Robinson, Angela L. 0000-0001-5845-4847","orcid":"https://orcid.org/0000-0001-5845-4847","contributorId":206329,"corporation":false,"usgs":true,"family":"Robinson","given":"Angela","email":"","middleInitial":"L.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":917597,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70260668,"text":"70260668 - 2024 - Neogene hydrothermal Fe- and Mn-oxide mineralization of Paleozoic continental rocks, Amerasia Basin, Arctic Ocean","interactions":[],"lastModifiedDate":"2024-11-07T16:21:49.717818","indexId":"70260668","displayToPublicDate":"2024-11-06T09:55:32","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1757,"text":"Geochemistry, Geophysics, Geosystems","active":true,"publicationSubtype":{"id":10}},"title":"Neogene hydrothermal Fe- and Mn-oxide mineralization of Paleozoic continental rocks, Amerasia Basin, Arctic Ocean","docAbstract":"<p><span>Rocks dredged from water depths of 1,605, 2,500, 3,300, and 3,400&nbsp;m in the Arctic Ocean included Paleozoic continental rocks pervasively mineralized during the Neogene by hydrothermal Fe and Mn oxides. Samples were recovered in three dredge hauls from the Chukchi Borderland and one from Mendeleev Ridge north of Alaska and eastern Siberia, respectively. Many of the rocks were so pervasively altered that the protolith could not be identified, while others had volcanic, plutonic, and metamorphic protoliths. The mineralized rocks were cemented and partly to wholly replaced by the hydrothermal oxides. The Amerasia Basin, where the Chukchi Borderland and Mendeleev Ridge occur, supports a series of faults and fractures that serve as major zones of crustal weakness. We propose that the stratabound hydrothermal deposits formed through the flux of hydrothermal fluids along Paleozoic and Mesozoic faults related to block faulting along a rifted margin during minor episodes of Neogene tectonism and were later exposed at the seafloor through slumping or other gravity processes. Tectonically driven hydrothermal circulation most likely facilitated the pervasive mineralization along fault surfaces via frictional heating, hydrofracturing brecciation, and low- to moderate temperature Fe- and Mn-rich hydrothermal fluids, which mineralized the crushed, altered, and brecciated rocks.</span></p>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2023GC010996","usgsCitation":"Hein, J.R., Mizell, K., and Gartman, A., 2024, Neogene hydrothermal Fe- and Mn-oxide mineralization of Paleozoic continental rocks, Amerasia Basin, Arctic Ocean: Geochemistry, Geophysics, Geosystems, v. 25, no. 11, e2023GC010996, 27 p., https://doi.org/10.1029/2023GC010996.","productDescription":"e2023GC010996, 27 p.","ipdsId":"IP-167891","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":466778,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2023gc010996","text":"Publisher Index Page"},{"id":463785,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Amerasia basin, Arctic Ocean","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -150,\n              72\n            ],\n            [\n              -179.9,\n              74.5\n            ],\n            [\n              -179.9,\n              85\n            ],\n            [\n              -137.09374278427933,\n              80.73796302105899\n            ],\n            [\n              -115,\n              73\n            ],\n            [\n              -150,\n              72\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              179.9,\n              85\n            ],\n            [\n              165,\n              85\n            ],\n            [\n              172,\n              74.5\n            ],\n            [\n              179.9,\n              74.5\n            ],\n            [\n              179.9,\n              85\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"25","issue":"11","noUsgsAuthors":false,"publicationDate":"2024-11-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Hein, James R. 0000-0002-5321-899X jhein@usgs.gov","orcid":"https://orcid.org/0000-0002-5321-899X","contributorId":140835,"corporation":false,"usgs":true,"family":"Hein","given":"James","email":"jhein@usgs.gov","middleInitial":"R.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":918141,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mizell, Kira 0000-0002-5066-787X kmizell@usgs.gov","orcid":"https://orcid.org/0000-0002-5066-787X","contributorId":4914,"corporation":false,"usgs":true,"family":"Mizell","given":"Kira","email":"kmizell@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":918142,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gartman, Amy 0000-0001-9307-3062 agartman@usgs.gov","orcid":"https://orcid.org/0000-0001-9307-3062","contributorId":177057,"corporation":false,"usgs":true,"family":"Gartman","given":"Amy","email":"agartman@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":918143,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70263425,"text":"70263425 - 2024 - Assessing and implementing the concept of Blue Economy in Laurentian Great Lakes fisheries: Lessons from coupled human and natural systems","interactions":[],"lastModifiedDate":"2025-02-11T15:30:07.537954","indexId":"70263425","displayToPublicDate":"2024-11-06T08:22:22","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":865,"text":"Aquatic Ecosystem Health & Management","active":true,"publicationSubtype":{"id":10}},"title":"Assessing and implementing the concept of Blue Economy in Laurentian Great Lakes fisheries: Lessons from coupled human and natural systems","docAbstract":"Inland fisheries often receive little to no attention in global discussions about sustainable development. The consequences of overlooking inland fisheries in sustainability dialogues are increasingly problematic as fisheries stressors (e.g., overharvest, species invasion, climate change, habitat modification) intensify. Elevating the global profile of inland fisheries requires an approach for quantifying and clearly conveying the ecological, economic, and societal values of these systems. One such approach involves the Blue Economy, a multifaceted concept initially used to describe the intersection of marine conservation and sustainable use of marine resources for economic growth. Although conceptually powerful, the Blue Economy has rarely been applied to inland waters and fisheries. To address this knowledge gap, we conceptualized Laurentian Great Lakes fisheries from a Blue Economy perspective. In particular, we evaluated the utility of the coupled human and natural systems (CHANS) framework for characterizing the ecological, economic, and societal values of Laurentian Great Lakes fisheries and associated contributions to the Blue Economy (e.g., human livelihoods, food security, recreation, conservation, economic prosperity). There are numerous opportunities to leverage CHANS methods (e.g., metacoupling, telecoupling) and associated mathematical models to advance fisheries science, inform fisheries management, and ultimately move toward a Blue Economy in the Laurentian Great Lakes. To that end, we demonstrated applications of CHANS methods, discussed strategies for communicating with stakeholders, and provided insights for navigating challenges to developing a Blue Economy in the Laurentian Great Lakes—a model that could be used in the African Great Lakes and other large ecosystems in the world.","language":"English","publisher":"BioOne","doi":"10.14321/aehm.027.02.74","usgsCitation":"Carlson, A.K., Leonard, N., Munawar, M., and Taylor, W., 2024, Assessing and implementing the concept of Blue Economy in Laurentian Great Lakes fisheries: Lessons from coupled human and natural systems: Aquatic Ecosystem Health & Management, v. 27, no. 2, p. 74-84, https://doi.org/10.14321/aehm.027.02.74.","productDescription":"11 p.","startPage":"74","endPage":"84","ipdsId":"IP-154893","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":481930,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","otherGeospatial":"Laurentian Great Lakes","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -91.35414421298296,\n              47.69798628255907\n            ],\n            [\n              -92.55498641328694,\n              46.29425302711437\n            ],\n            [\n              -86.95944652656331,\n              46.00505185703939\n            ],\n            [\n              -88.62282303782777,\n              43.92021164632037\n            ],\n            [\n              -87.50058525109819,\n              41.25347232284972\n            ],\n            [\n              -85.72809349640711,\n              42.11694323111757\n            ],\n            [\n              -85.91733849617773,\n              43.493974004776575\n            ],\n            [\n              -84.89672932891068,\n              44.873597615031386\n            ],\n            [\n              -83.29102906108528,\n              43.6549891230233\n            ],\n            [\n              -83.78159647699495,\n              41.31847374004327\n            ],\n            [\n              -79.95408136104199,\n              41.39215071916226\n            ],\n            [\n              -75.87519895574565,\n              43.702579861752696\n            ],\n            [\n              -79.58470723400637,\n              45.3214766230865\n            ],\n            [\n              -84.23758896005683,\n              48.14783853442674\n            ],\n            [\n              -88.84558873081599,\n              49.05585075889549\n            ],\n            [\n              -91.35414421298296,\n              47.69798628255907\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"27","issue":"2","noUsgsAuthors":false,"publicationDate":"2024-04-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Carlson, Andrew Kenneth 0000-0002-6681-0853","orcid":"https://orcid.org/0000-0002-6681-0853","contributorId":340581,"corporation":false,"usgs":true,"family":"Carlson","given":"Andrew","email":"","middleInitial":"Kenneth","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":926955,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Leonard, Nancy J.","contributorId":350769,"corporation":false,"usgs":false,"family":"Leonard","given":"Nancy J.","affiliations":[{"id":20304,"text":"Pacific States Marine Fisheries Commission","active":true,"usgs":false}],"preferred":false,"id":926956,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Munawar, Mohiuddin","contributorId":350770,"corporation":false,"usgs":false,"family":"Munawar","given":"Mohiuddin","affiliations":[{"id":13677,"text":"Fisheries and Oceans Canada","active":true,"usgs":false}],"preferred":false,"id":926957,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Taylor, William W.","contributorId":350772,"corporation":false,"usgs":false,"family":"Taylor","given":"William W.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":926958,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70261558,"text":"70261558 - 2024 - Insights on arc magmatic systems drawn from natural melt inclusions and crystallization experiments at P<sub>H2O</sub>=800 MPa under oxidizing conditions","interactions":[],"lastModifiedDate":"2024-12-16T14:12:30.156142","indexId":"70261558","displayToPublicDate":"2024-11-06T06:57:05","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2420,"text":"Journal of Petrology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Insights on arc magmatic systems drawn from natural melt inclusions and crystallization experiments at P<sub>H2O</sub>=800 MPa under oxidizing conditions","title":"Insights on arc magmatic systems drawn from natural melt inclusions and crystallization experiments at P<sub>H2O</sub>=800 MPa under oxidizing conditions","docAbstract":"<p>Whole rock compositions at Buldir Volcano, western Aleutian arc, record a strong, continuous trend of iron depletion with decreasing MgO, classically interpreted as a calc-alkaline liquid line of descent. In contrast, olivine-hosted melt inclusions have higher total iron (FeO<sup>*</sup>) than whole rocks and show little change in FeO* with decreasing MgO. To investigate this discrepancy and determine the conditions required for strong iron depletion, we conducted oxygen fugacity (ƒO<sub>2</sub>) buffered, water-saturated crystallization experiments at 800 MPa and ƒO<sub>2</sub> = QFM + 1.6 ± 0.4 (1σ⁠) (where QFM refers to the quartz-fayalite-magnetite buffer) on a high-Al, basaltic starting material modeled after a Buldir lava. Experimental conditions were informed by olivine-hosted melt inclusions that record minimum entrapment pressures as high as 570 MPa, &gt;6 wt % H2O, and ƒO<sub>2</sub> of QFM + 1.4 (±0.2), making Buldir one of the most oxidized and wettest arc volcanoes documented globally. The experiments produce melts with Si-enrichment and Fe-depletion signatures characteristic of evolved, calc-alkaline magmas at the lowest MgO, although FeO<sup>*</sup> remains roughly constant over most of the experimental temperature range. Experiments saturate CrAl-spinel and olivine at 1160°C, followed by clinopyroxene and Al-spinel at 1085°C, hornblende at 1060°C, and, finally, plagioclase and magnetite between 1040°C and 960°C. Hornblende crystallization, not magnetite, generates the largest increase in SiO2 and largest decrease in FeO<sup>*</sup> in coexisting melts. Compositions of melt inclusions are consistent with experimental melts and reflect crystallization of a basaltic parent magma at high P<sub>H2O</sub>. In contrast, the whole rock compositional trends are influenced by magma mixing and phenocryst redistribution and accumulation. The crystallization experiments and natural liquids (melt inclusions and groundmass glass) from Buldir suggest that for an oxidized, hydrous primary basalt starting composition, significant Fe depletion from the melt will not occur until intermediate to late stages of magma crystallization (&lt; ~4.5 wt % MgO). We conclude that the Buldir whole rock trend cannot be reproduced by crystallization at arc-relevant oxygen fugacities and is not a true liquid line of descent, warranting caution when interpreting volcanic trends globally.</p>","language":"English","publisher":"Oxford University Press","doi":"10.1093/petrology/egae117","usgsCitation":"Andrys, J.L., Cottrell, E., Kelley, K., Waters, L.E., and Coombs, M.L., 2024, Insights on arc magmatic systems drawn from natural melt inclusions and crystallization experiments at P<sub>H2O</sub>=800 MPa under oxidizing conditions: Journal of Petrology, v. 65, no. 12, egae117, 23 p., https://doi.org/10.1093/petrology/egae117.","productDescription":"egae117, 23 p.","ipdsId":"IP-166029","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":465141,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"65","issue":"12","noUsgsAuthors":false,"publicationDate":"2024-11-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Andrys, Janine L.","contributorId":347200,"corporation":false,"usgs":false,"family":"Andrys","given":"Janine","email":"","middleInitial":"L.","affiliations":[{"id":52668,"text":"Boise State","active":true,"usgs":false}],"preferred":false,"id":921044,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cottrell, Elizabeth","contributorId":347203,"corporation":false,"usgs":false,"family":"Cottrell","given":"Elizabeth","affiliations":[{"id":36606,"text":"Smithsonian Institution","active":true,"usgs":false}],"preferred":false,"id":921045,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kelley, Katherine A.","contributorId":347206,"corporation":false,"usgs":false,"family":"Kelley","given":"Katherine A.","affiliations":[{"id":6922,"text":"University of Rhode Island","active":true,"usgs":false}],"preferred":false,"id":921046,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Waters, Laura E.","contributorId":347209,"corporation":false,"usgs":false,"family":"Waters","given":"Laura","email":"","middleInitial":"E.","affiliations":[{"id":34868,"text":"New Mexico Institute of Mining and Technology","active":true,"usgs":false}],"preferred":false,"id":921047,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Coombs, Michelle L. 0000-0002-6002-6806 mcoombs@usgs.gov","orcid":"https://orcid.org/0000-0002-6002-6806","contributorId":2809,"corporation":false,"usgs":true,"family":"Coombs","given":"Michelle","email":"mcoombs@usgs.gov","middleInitial":"L.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":921048,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70268340,"text":"70268340 - 2024 - River suspended-sand flux computation with uncertainty estimation using water samples and high-resolution ADCP measurements","interactions":[],"lastModifiedDate":"2025-06-23T14:40:02.847232","indexId":"70268340","displayToPublicDate":"2024-11-05T09:37:01","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7942,"text":"Earth Surface Dynamics","active":true,"publicationSubtype":{"id":10}},"title":"River suspended-sand flux computation with uncertainty estimation using water samples and high-resolution ADCP measurements","docAbstract":"<p><span>Measuring suspended-sand fluxes in rivers remains a scientific challenge due to their high spatial and temporal variability. To capture the vertical and lateral gradients of concentration in the cross-section, measurements with point samples are performed. However, the uncertainty related to these measurements is rarely evaluated, as few studies of the major sources of error exist. Therefore, the aim of this study is to develop a method to determine the cross-sectional sand flux and estimate its uncertainty. This SDC (for sand discharge computing) method combines suspended-sand concentrations from point samples with ADCP (acoustic Doppler current profiler) high-resolution depth and velocity measurements. The MAP (for multitransect averaged profile) method allows obtaining an average of several ADCP transects on a regular grid, including the unmeasured areas. The suspended-sand concentrations are integrated vertically by fitting a theoretical exponential suspended-sand profile to the data using Bayesian modeling. The lateral integration is based on the water depth as a proxy for the local bed shear stress to evaluate the bed concentration and sediment diffusion along the river cross-section. The estimation of uncertainty combines ISO standards and semi-empirical methods with a Bayesian approach to estimate the uncertainty due to the vertical integration. The new method is applied to data collected in four rivers under various hydro-sedimentary conditions: the Colorado, Rhône, Isère, and Amazon rivers, with computed flux uncertainties ranging between 18 % and 32 %. The relative difference between the suspended-sand flux in 21 cases calculated with the proposed SDC method compared to the International Organization for Standardization (ISO) 4363 standard method ranges between&nbsp;</span><span class=\"inline-formula\">−</span><span>40 % and&nbsp;</span><span class=\"inline-formula\">+</span><span>23 %. This method that comes with a flexible, open-source code is the first to propose an applicable uncertainty estimation that could be adapted to other flux computation methods.</span></p>","language":"English","publisher":"European Geophysical Union","doi":"10.5194/esurf-12-1243-2024","usgsCitation":"Marggraf, J., Dramais, G., Le Coz, J., Calmel, B., Camenen, B., Topping, D.J., Santini, W., Pierrefeu, G., and Lauters, F., 2024, River suspended-sand flux computation with uncertainty estimation using water samples and high-resolution ADCP measurements: Earth Surface Dynamics, v. 12, no. 6, p. 1243-1266, https://doi.org/10.5194/esurf-12-1243-2024.","productDescription":"24 p.","startPage":"1243","endPage":"1266","ipdsId":"IP-123898","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":491495,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/esurf-12-1243-2024","text":"Publisher Index Page"},{"id":491101,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"12","issue":"6","noUsgsAuthors":false,"publicationDate":"2024-11-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Marggraf, Jessica","contributorId":350702,"corporation":false,"usgs":false,"family":"Marggraf","given":"Jessica","affiliations":[{"id":83813,"text":"RiverLy, INRAE, 5 Rue de la Doua, Villeurbanne, 69100, France","active":true,"usgs":false}],"preferred":false,"id":940855,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dramais, Guillaume","contributorId":357236,"corporation":false,"usgs":false,"family":"Dramais","given":"Guillaume","affiliations":[{"id":85354,"text":"1RiverLy, INRAE, 5 Rue de la Doua, Villeurbanne, 69100, France","active":true,"usgs":false}],"preferred":false,"id":940856,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Le Coz, Jerome","contributorId":350703,"corporation":false,"usgs":false,"family":"Le Coz","given":"Jerome","affiliations":[{"id":83813,"text":"RiverLy, INRAE, 5 Rue de la Doua, Villeurbanne, 69100, France","active":true,"usgs":false}],"preferred":false,"id":940857,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Calmel, Blaise","contributorId":357237,"corporation":false,"usgs":false,"family":"Calmel","given":"Blaise","affiliations":[{"id":85354,"text":"1RiverLy, INRAE, 5 Rue de la Doua, Villeurbanne, 69100, France","active":true,"usgs":false}],"preferred":false,"id":940858,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Camenen, Benoit","contributorId":238956,"corporation":false,"usgs":false,"family":"Camenen","given":"Benoit","email":"","affiliations":[{"id":47840,"text":"Scientist, IRSTEA, Lyon, France","active":true,"usgs":false}],"preferred":false,"id":940859,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Topping, David J. 0000-0002-2104-4577","orcid":"https://orcid.org/0000-0002-2104-4577","contributorId":215068,"corporation":false,"usgs":true,"family":"Topping","given":"David","middleInitial":"J.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":940860,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Santini, William","contributorId":357238,"corporation":false,"usgs":false,"family":"Santini","given":"William","affiliations":[{"id":85355,"text":"IRD-GET, Institut de Recherche pour le Développement, Laboratoire GET (IRD, CNRS, UPS, CNES), Toulouse, France","active":true,"usgs":false}],"preferred":false,"id":940861,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Pierrefeu, Gilles","contributorId":238958,"corporation":false,"usgs":false,"family":"Pierrefeu","given":"Gilles","email":"","affiliations":[{"id":47841,"text":"Senior Engineer, CNR, Lyon, France","active":true,"usgs":false}],"preferred":false,"id":940862,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Lauters, François","contributorId":357239,"corporation":false,"usgs":false,"family":"Lauters","given":"François","affiliations":[{"id":85356,"text":"Service Etudes Eau Environnement, EDF, 134 Chemin de l'étang, Saint Martin Le Vinoux, 38950, France","active":true,"usgs":false}],"preferred":false,"id":940863,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70260957,"text":"70260957 - 2024 - Reducing uncertainty with iterative model updating parses effects of competition and environment on salamander occupancy","interactions":[],"lastModifiedDate":"2024-12-10T15:37:31.896607","indexId":"70260957","displayToPublicDate":"2024-11-05T09:14:46","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2932,"text":"Oecologia","active":true,"publicationSubtype":{"id":10}},"title":"Reducing uncertainty with iterative model updating parses effects of competition and environment on salamander occupancy","docAbstract":"<p>Making timely management decisions is often hindered by uncertainty. Monitoring reduces two key types of uncertainty. First, it serves to reduce structural uncertainty of how the system works and provides support for expectations of how a system works. Second, it serves to reduce parametric uncertainty of the drivers of system dynamics. By combining monitoring data and quantitative models, we can reduce structural and parametric uncertainty. To demonstrate this, we focus on the Shenandoah salamander (<i>Plethodon</i> <i>shenandoah</i>), a United States Federally Endangered Species. Early work suggested that <i>P. shenandoah</i> extinction risk results from competition with a conspecific (<i>Plethodon cinereus</i>). However, more recent work has found equivocal support for this claim, instead suggesting that abiotic factors, such as moisture and temperature, drive <i>P. shenandoah</i> persistence. Using long-term monitoring data, we find that while competition may play a part in <i>P. shenandoah</i> extinction risk, measures of surface moisture are better predictors of occupancy dynamics. Further, we find decreased detection rates of <i>P. shenandoah</i> when <i>P. cinereus</i> is present, suggesting a conflation of detection probability with actual competition, which cautions against making inference from unadjusted observations of occurrence. Using multiple lines of inquiry allows for more robust understanding of system drivers in the face of high uncertainty, increasing opportunities to manage extinction risk.</p>","language":"English","publisher":"Springer Nature","doi":"10.1007/s00442-024-05631-x","usgsCitation":"Werba, J.A., DiRenzo, G.V., Brand, A., and Campbell Grant, E.H., 2024, Reducing uncertainty with iterative model updating parses effects of competition and environment on salamander occupancy: Oecologia, v. 206, p. 305-316, https://doi.org/10.1007/s00442-024-05631-x.","productDescription":"12 p.","startPage":"305","endPage":"316","ipdsId":"IP-148195","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":464231,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Virginia","otherGeospatial":"Blue Ridge Mountains, Shenandoah National Park","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -78.60935855780521,\n              38.68748637317097\n            ],\n            [\n              -78.60935855780521,\n              38.31093059502825\n            ],\n            [\n              -78.13191468279777,\n              38.31093059502825\n            ],\n            [\n              -78.13191468279777,\n              38.68748637317097\n            ],\n            [\n              -78.60935855780521,\n              38.68748637317097\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"206","noUsgsAuthors":false,"publicationDate":"2024-11-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Werba, Jo Avital 0000-0002-5295-7790","orcid":"https://orcid.org/0000-0002-5295-7790","contributorId":338728,"corporation":false,"usgs":true,"family":"Werba","given":"Jo","email":"","middleInitial":"Avital","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":918691,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"DiRenzo, Graziella Vittoria 0000-0001-5264-4762","orcid":"https://orcid.org/0000-0001-5264-4762","contributorId":243404,"corporation":false,"usgs":true,"family":"DiRenzo","given":"Graziella","email":"","middleInitial":"Vittoria","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":918692,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brand, Adrianne 0000-0003-2664-0041","orcid":"https://orcid.org/0000-0003-2664-0041","contributorId":304281,"corporation":false,"usgs":true,"family":"Brand","given":"Adrianne","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":918693,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Campbell Grant, Evan H. 0000-0003-4401-6496 ehgrant@usgs.gov","orcid":"https://orcid.org/0000-0003-4401-6496","contributorId":150443,"corporation":false,"usgs":true,"family":"Campbell Grant","given":"Evan","email":"ehgrant@usgs.gov","middleInitial":"H.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":918694,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70261018,"text":"70261018 - 2024 - Ceanothus: Taxonomic patterns in life history responses to fire","interactions":[],"lastModifiedDate":"2024-12-10T15:36:47.620254","indexId":"70261018","displayToPublicDate":"2024-11-05T08:14:43","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":724,"text":"American Journal of Botany","active":true,"publicationSubtype":{"id":10}},"title":"Ceanothus: Taxonomic patterns in life history responses to fire","docAbstract":"<p>Premise: <i>Ceanothus</i><span>&nbsp;(Rhamnaceae) is a large genus of shrubs that dominate California chaparral and are resilient to fires. Persistence is ensured by resprouting and/or seedling recruitment from dormant seed banks. Some species do both and others, the obligate seeders, are entirely dependent on seedling recruitment. The distribution of these two modes within the genus is poorly documented.</span></p><p>Methods: <span>We used all available publications that document species responses to fire and filled most gaps in the literature based on extensive field studies of more than 60 recent wildfires in California.</span></p><p>Results: <span>The genus is divided into two subgenera,&nbsp;</span><i>Ceanothus</i><span>&nbsp;and&nbsp;</span><i>Cerastes</i><span>.&nbsp;</span><i>Ceanothus</i><span>&nbsp;is widely considered to comprise mostly resprouting species and&nbsp;</span><i>Cerastes</i><span>&nbsp;to consist of only obligate seeders. The subgenus&nbsp;</span><i>Ceanothus</i><span>&nbsp;includes resprouting species throughout their range from the eastern United States and Midwest to western United States. Within the California Floristic Province (CFP), a few species are unique in producing massive lignotubers that develop from repeated fires; however, within the CFP, the majority of species in this subgenus do not resprout and are obligate seeders. Two have disjunct subspecies that are facultative seeders or obligate seeders.</span></p><p>Conclusions: <span>Previously, speciation in this genus was contended to have occurred in the late Miocene within the CFP. The syndrome of obligate seeding is most strongly represented in this region, and we hypothesize that evolution of this syndrome was a response to increased predictability of fire driven by the Mediterranean climate and the long interval between fires.</span></p>","language":"English","publisher":"Botanical Society of America","doi":"10.1002/ajb2.16434","usgsCitation":"Keeley, J., Parker, V.T., Zedler, P., and Pratt, R., 2024, Ceanothus: Taxonomic patterns in life history responses to fire: American Journal of Botany, v. 111, no. 11, e16434, https://doi.org/10.1002/ajb2.16434.","productDescription":"e16434","ipdsId":"IP-163254","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":466783,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ajb2.16434","text":"Publisher Index 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,{"id":70261113,"text":"70261113 - 2024 - Advancing water security in Africa with new high-resolution discharge data","interactions":[],"lastModifiedDate":"2024-11-25T15:30:11.60969","indexId":"70261113","displayToPublicDate":"2024-11-05T08:00:49","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3907,"text":"Scientific Data","active":true,"publicationSubtype":{"id":10}},"title":"Advancing water security in Africa with new high-resolution discharge data","docAbstract":"<p>VegDischarge v1 is a comprehensive river discharge across Africa (2000–2021), produced by coupling the agro-hydrologic VegET model and the mizuRoute routing framework. Using remote sensing data and hydrological modeling, the 1-km runoff field simulated by VegET, and routed with mizuRoute, covers over 64,000 river segments in Africa. The VegET model simulates runoff based on vegetation and soil moisture dynamics, while mizuRoute processes this runoff through a detailed river network. Performance metrics show strong model reliability, with R² ranging from 0.5 to 0.9, NSE between 0.6 and 0.9, and KGE from 0.5 to 0.8. The total annual average discharge for Africa is quantified at 3238.1 km³<sup>.</sup>year-1, with contributions to various oceanic basins: 989.9 km³<sup>.</sup>year-1 to the North Atlantic, primarily from West African rivers like the Senegal, Gambia, Volta, and Niger; 1313.7 km³<sup>.</sup>year-1 to the South Atlantic, largely from the Congo River; 212.5 km³<sup>.</sup>year-1 to the Mediterranean Sea, predominantly from the Nile River; and 722.0 km³<sup>.</sup>year-1 to the Indian Ocean, with substantial inputs from rivers such as the Zambezi. This VegDischarge v1 is valuable for policymakers, stakeholders, and researchers to better understand water availability, its temporal and spatial variations, that impact water-related infrastructure planning, sustainable resource allocation, and the development of climate resilience mitigation strategies.</p>","language":"English","publisher":"Springer Nature","doi":"10.1038/s41597-024-04034-0","usgsCitation":"Akpoti, K., Velpuri, N., Mizukami, N., Kagone, S., Leh, M., Mekonnen, K., Owusu, A., Tinonetsana, P., Phiri, M., Madushanka, L., Perera, T., Prabhath, P.T., Parrish, G.E., Senay, G.B., and Seid, A., 2024, Advancing water security in Africa with new high-resolution discharge data: Scientific Data, v. 11, 1195, 23 p., https://doi.org/10.1038/s41597-024-04034-0.","productDescription":"1195, 23 p.","ipdsId":"IP-163078","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) 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,{"id":70265940,"text":"70265940 - 2024 - Long-term trends in abundance and potential drivers for eight species of coastal birds in the U.S. South Atlantic","interactions":[],"lastModifiedDate":"2025-04-22T17:18:09.018356","indexId":"70265940","displayToPublicDate":"2024-11-04T12:13:22","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5094,"text":"Regional Studies in Marine Science","onlineIssn":"2352-4855","active":true,"publicationSubtype":{"id":10}},"title":"Long-term trends in abundance and potential drivers for eight species of coastal birds in the U.S. South Atlantic","docAbstract":"<p><span>The U.S. South Atlantic coastal region is used by many marine birds for foraging, reproduction, and migration. We developed standardized indices of relative abundance from long–term (1980–2016), semi-structured monitoring data (eBird) for eight species: Brown Pelican (</span><i>Pelecanus occidentalis</i><span>), Double-Crested Cormorant (</span><i>Nannopterum auritum</i><span>), White Ibis (</span><i>Eudocimus albus</i><span>), Wood Stork (</span><i>Mycteria americana</i><span>), Piping Plover (</span><i>Charadrius melodus</i><span>), American Oystercatcher (</span><i>Haematopus palliatus</i><span>), Clapper Rail (</span><i>Rallus crepitans</i><span>), and Northern Gannet (</span><i>Morus bassanus</i><span>). Following a period of stable or declining abundance from the 1980s through the 1990s, most species have shown stable or slightly upward trends through the late 2000s; Brown Pelican and Piping Plover have shown some evidence of recent declines. Species–specific correlations between abundance indices developed from presence/absence data and those developed from count data were positive for all species and ranged from 0.53 to 0.86. Dynamic factor analysis identified common trends in abundance among several species, in particular, Brown Pelican, Double–Crested Cormorant, and White Ibis. Model performance was improved with inclusion of an indicator of sea level rise, but not forage fish abundance or temperature, indicating habitat availability mediated by changing water levels may explain some of the underlying abundance trends. Our results provide baseline information on long–term trends for several important coastal birds that can help inform research, monitoring and conservation efforts in the U.S. South Atlantic region.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.rsma.2024.103886","usgsCitation":"Craig, J., Siegfried, K., Cheshire, R., Karnauskas, M., and Jodice, P.G., 2024, Long-term trends in abundance and potential drivers for eight species of coastal birds in the U.S. South Atlantic: Regional Studies in Marine Science, v. 80, 103886, 14 p., https://doi.org/10.1016/j.rsma.2024.103886.","productDescription":"103886, 14 p.","ipdsId":"IP-159778","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":490995,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.rsma.2024.103886","text":"Publisher Index Page"},{"id":484853,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida, Georgia, North Carolina, South Carolina","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -80.63812689012559,\n              24.981195366830136\n            ],\n            [\n              -79.74779294326453,\n              26.53588076270711\n            ],\n            [\n              -81.03973835977342,\n              29.95801011198671\n            ],\n            [\n              -81.11631302916135,\n              31.396072044056297\n            ],\n            [\n              -79.30822669011008,\n              33.150807571917255\n            ],\n            [\n              -76.01718491915142,\n              34.68241756177868\n            ],\n            [\n              -75.87971328976948,\n              36.709011056016635\n            ],\n            [\n              -78.23890913908112,\n              36.73325180728209\n            ],\n            [\n              -80.34864182194866,\n              34.55119531258265\n            ],\n            [\n              -83.32101866451728,\n              32.39789594150341\n            ],\n            [\n              -81.81661133200153,\n              28.946064586607065\n            ],\n            [\n              -80.63812689012559,\n              24.981195366830136\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"80","noUsgsAuthors":false,"publicationDate":"2024-11-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Craig, J.K.","contributorId":353621,"corporation":false,"usgs":false,"family":"Craig","given":"J.K.","affiliations":[{"id":36612,"text":"National Marine Fisheries Service","active":true,"usgs":false}],"preferred":false,"id":934109,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Siegfried, K.I.","contributorId":353620,"corporation":false,"usgs":false,"family":"Siegfried","given":"K.I.","affiliations":[{"id":36612,"text":"National Marine Fisheries Service","active":true,"usgs":false}],"preferred":false,"id":934108,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cheshire, R.T.","contributorId":353622,"corporation":false,"usgs":false,"family":"Cheshire","given":"R.T.","affiliations":[{"id":36612,"text":"National Marine Fisheries Service","active":true,"usgs":false}],"preferred":false,"id":934110,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Karnauskas, M.","contributorId":353623,"corporation":false,"usgs":false,"family":"Karnauskas","given":"M.","affiliations":[{"id":36612,"text":"National Marine Fisheries Service","active":true,"usgs":false}],"preferred":false,"id":934111,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jodice, Patrick G.R. 0000-0001-8716-120X","orcid":"https://orcid.org/0000-0001-8716-120X","contributorId":219852,"corporation":false,"usgs":true,"family":"Jodice","given":"Patrick","middleInitial":"G.R.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":934112,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70260490,"text":"70260490 - 2024 - The state of the science and practice of stream restoration in the Chesapeake: Lessons learned to inform better implementation, assessment and outcomes","interactions":[],"lastModifiedDate":"2024-11-05T16:47:15.828836","indexId":"70260490","displayToPublicDate":"2024-11-04T10:44:08","publicationYear":"2024","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":3,"text":"Organization Series"},"seriesTitle":{"id":17129,"text":"STAC Workshop Report","active":true,"publicationSubtype":{"id":3}},"seriesNumber":"24-006","title":"The state of the science and practice of stream restoration in the Chesapeake: Lessons learned to inform better implementation, assessment and outcomes","docAbstract":"The Chesapeake Bay Program’s (CBP) Science and Technical Advisory Committee (STAC) organized and led a workshop on the science and practice of stream restoration in order to summarize the state of knowledge in order to identify ways to improve stream restoration outcomes. The workshop identified a general framework for explaining the main factors leading to stream restoration outcomes: stream degradation has occurred, leading to regulatory and policy motivations that prioritize project goals, which leads to restoration approaches, assessment and monitoring efforts, and ultimately stream restoration outcomes. In the Chesapeake Bay watershed, stream restoration often occurs in response to Clean Water Act (CWA) mandates to reduce nitrogen, phosphorus, and sediment loads to the Bay. Reviews of stream restoration outcomes summarized at the workshop showed that, in general, stream restorations have led to minimal improvement to stream aquatic biota, effective ‘stabilization’ of channel form over time, moderate improvements to water quality, and short-term negative impacts to riparian vegetation. \n\n\nThe fundamental finding of the workshop was that often the primary goal of stream restoration projects is to improve geomorphic stability in the restored reach and downstream water quality, and not to improve local ecological conditions through ‘uplift’ (improvement of one or more ecosystem functions through a restorative activity; a term defined in Appendix D), and therefore these projects often do not improve aquatic macroinvertebrate or fish communities. This conflict in goals is a shortcoming of the currently most common regulatory driver for stream restoration (reducing downstream loads of N, P, and sediment) that could be addressed directly through diversifying goals to include biotic uplift, as biological benefit is an assumed condition for the permitting and crediting of stream restoration projects. It is also likely that current understanding of stressors and drivers of stream ecosystem health is insufficient, and that reach-scale restoration focused on geomorphic restoration is not removing the actual sources of stream health impairment that may arise in the upstream watershed. More science could help to identify how to improve the ecological condition of streams through management. The outcome of stream restoration monitoring has revealed that while geomorphic and hydrodynamic functions of stream restoration projects may be achieved, biotic stream function improvements remain elusive. As such, ensuring uplift may be achieved by avoiding restoration projects that risk resources in higher-quality streams and riparian corridors. Reach-scale restoration often does not effectively mitigate the watershed-scale stressors of stream ecosystems. If a desired outcome of stream restoration includes ecological uplift, then focusing efforts on improving stream ecology could help meet that goal.","language":"English","publisher":"Chesapeake Bay Program","collaboration":"Chesapeake Bay Program","usgsCitation":"Noe, G.E., Law, N., Berger, J., Filoso, S., Drescher, S., Fraley-McNeal, L., Hayes, B., Mayer, P., Ruck, C., Stack, B., Starr, R., Stranko, S., and Thompson, T., 2024, The state of the science and practice of stream restoration in the Chesapeake: Lessons learned to inform better implementation, assessment and outcomes: STAC Workshop Report 24-006, 96 p.","productDescription":"96 p.","ipdsId":"IP-169302","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":463690,"rank":1,"type":{"id":15,"text":"Index 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Scott","contributorId":337238,"corporation":false,"usgs":false,"family":"Stranko","given":"Scott","affiliations":[{"id":33964,"text":"Maryland Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":917875,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Thompson, Tess","contributorId":345928,"corporation":false,"usgs":false,"family":"Thompson","given":"Tess","email":"","affiliations":[{"id":12694,"text":"Virginia Tech","active":true,"usgs":false}],"preferred":false,"id":917876,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}}
,{"id":70260488,"text":"70260488 - 2024 - Individual return patterns of spawning flannelmouth sucker (Catostomus latipinnis) to a desert river tributary","interactions":[],"lastModifiedDate":"2024-11-05T16:05:17.434171","indexId":"70260488","displayToPublicDate":"2024-11-04T09:59:54","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3358,"text":"Scientific Reports","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Individual return patterns of spawning flannelmouth sucker (<i>Catostomus latipinnis</i>) to a desert river tributary","title":"Individual return patterns of spawning flannelmouth sucker (Catostomus latipinnis) to a desert river tributary","docAbstract":"<p><span>Tributaries provide temporal and spatial habitat heterogeneity in river networks that can be critical for parts of the life history of a species. Tributary fidelity can benefit individual fish undergoing spawning migrations by reducing time and energy spent exploring new areas and leveraging previous experience, but anthropogenic activities that fragment or degrade these systems can eliminate those benefits. We used multistate models based on passive integrated transponder (PIT) detection data from 2013 to 2023 to estimate the proportion of flannelmouth suckers (</span><i>Catostomus latipinnis</i><span>) migrating to a tributary, McElmo Creek, from the mainstem San Juan River for spawning. Survival varied among years and among states. The top model for migration probability included sex, with males slightly more likely to migrate (0.93 vs 0.90), and the next model identified interannual variation in migration probability ranging from 0.875 to 0.999 across years, indicating high site fidelity. Individuals showed consistency in relative arrival timing across years, with the highest correlation generally during years with greater spring discharge and extended tributary residence time. Successful tributary spawning may be important for the maintenance of the mainstem San Juan River flannelmouth sucker population, but site fidelity may be maladaptive where tributaries are vulnerable to human alterations.</span></p>","language":"English","publisher":"Nature","doi":"10.1038/s41598-024-72273-7","usgsCitation":"Bonjour, S.M., Gido, K., Cathcart, C.N., and McKinstry, M.C., 2024, Individual return patterns of spawning flannelmouth sucker (Catostomus latipinnis) to a desert river tributary: Scientific Reports, v. 14, no. 1, 26690, 12 p., https://doi.org/10.1038/s41598-024-72273-7.","productDescription":"26690, 12 p.","ipdsId":"IP-166408","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":466786,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-024-72273-7","text":"Publisher Index Page"},{"id":463698,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, Colorado, New Mexico, Utah","otherGeospatial":"Colorado River, McElmo Creek, San Juan River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -112,\n              38\n            ],\n            [\n              -112,\n              36.5\n            ],\n            [\n              -107,\n              36.5\n            ],\n            [\n              -107,\n              38\n            ],\n            [\n              -112,\n              38\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"14","issue":"1","noUsgsAuthors":false,"publicationDate":"2024-11-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Bonjour, Sophia Marie 0000-0003-3614-7023","orcid":"https://orcid.org/0000-0003-3614-7023","contributorId":335936,"corporation":false,"usgs":true,"family":"Bonjour","given":"Sophia","email":"","middleInitial":"Marie","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":917859,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gido, Keith B.","contributorId":341429,"corporation":false,"usgs":false,"family":"Gido","given":"Keith B.","affiliations":[{"id":12661,"text":"Kansas State University","active":true,"usgs":false}],"preferred":false,"id":917860,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cathcart, Charles N.","contributorId":317814,"corporation":false,"usgs":false,"family":"Cathcart","given":"Charles","email":"","middleInitial":"N.","affiliations":[{"id":7058,"text":"Alaska Department of Fish and Game","active":true,"usgs":false}],"preferred":false,"id":917861,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McKinstry, Mark C.","contributorId":301155,"corporation":false,"usgs":false,"family":"McKinstry","given":"Mark","email":"","middleInitial":"C.","affiliations":[{"id":65322,"text":"Upper Colorado Regional Office","active":true,"usgs":false}],"preferred":false,"id":917862,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70265637,"text":"70265637 - 2024 - A new water temperature modeling approach to predict thermal habitat suitability for nonnative cichlids in Florida rivers","interactions":[],"lastModifiedDate":"2025-04-14T15:41:33.931061","indexId":"70265637","displayToPublicDate":"2024-11-03T10:37:41","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2299,"text":"Journal of Freshwater Ecology","active":true,"publicationSubtype":{"id":10}},"title":"A new water temperature modeling approach to predict thermal habitat suitability for nonnative cichlids in Florida rivers","docAbstract":"<p><span>As global temperatures increase, the spatiotemporal arrangement of thermal habitats in Florida rivers may shift, creating the potential for greater dispersal and establishment of nonnative tropical freshwater fishes. To understand how water temperature changes may affect the spatial distribution of these nonnative species, more effective water temperature prediction models are necessary. Currently, most models employ either a generalized air–water temperature relationship or require expensive and complicated tools to measure hydrometeorological factors (e.g. groundwater input). Thus, we developed a novel modeling approach that is accurate, accessible, and cost-effective in allowing fisheries managers to project water temperatures in rivers across Central and North Florida. To characterize the potential for nonnative fishes to spread northward, we evaluated two hardy and abundant species currently found primarily in South Florida: Mayan Cichlid (</span><i>Mayaheros urophthalmus</i><span>) and Oscar (</span><i>Astronotus ocellatus</i><span>). Our results show an increase in thermally suitable winter days for both species in 10 of 11 rivers studied, consistent with predicted water temperature warming under 16 climate-change scenarios spanning different levels of air temperature warming (+1 °C, +2 °C, +3 °C, +4 °C) and precipitation/groundwater thermal sensitivity (0, 0.33, 0.66, 1). Considering resource limitations, fisheries managers can use our water temperature modeling approach to predict effects of climate change on Mayan Cichlid and Oscar survival, growth, and dispersal and take actions to manage potential northward movement of these species.</span></p>","language":"English","publisher":"Taylor & Francis","doi":"10.1080/02705060.2024.2405721","usgsCitation":"Scott, A., and Carlson, A.K., 2024, A new water temperature modeling approach to predict thermal habitat suitability for nonnative cichlids in Florida rivers: Journal of Freshwater Ecology, v. 39, no. 1, 2405721, 24 p., https://doi.org/10.1080/02705060.2024.2405721.","productDescription":"2405721, 24 p.","ipdsId":"IP-166869","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":488211,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1080/02705060.2024.2405721","text":"Publisher Index 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,{"id":70263176,"text":"70263176 - 2024 - Exploring the dynamic interactions between the Southern San Andreas Fault and a normal fault under the Salton Sea","interactions":[],"lastModifiedDate":"2025-01-31T15:08:50.504738","indexId":"70263176","displayToPublicDate":"2024-11-02T08:00:40","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":6453,"text":"Journal of Geophysical Research Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"Exploring the dynamic interactions between the Southern San Andreas Fault and a normal fault under the Salton Sea","docAbstract":"<p><span>We investigate the dynamic interactions between the Southern San Andreas Fault (SSAF) and a proximal normal fault (NF) beneath the Salton Sea in southern California. The NF, positioned near the SSAF terminus at Bombay Beach, exhibits 11–15 displacement events across 14 stratigraphic sequences, with a range of 0.2–1.4&nbsp;m of vertical offset since ∼2–3&nbsp;ka. Notably, four of these events may align temporally with SSAF earthquakes, raising questions about the possible interplay between the two faults. Utilizing dynamic rupture models, we analyze the coseismic interactions between the SSAF and NF, addressing under what conditions the SSAF induces slip on the NF. Our findings reveal that a suite of SSAF ruptures, particularly those propagating from north to south, can trigger slip on the normal fault and replicate observed vertical offsets. If the SSAF extends beneath the Salton Sea, earthquakes originating south of the NF intersection are less likely to trigger normal fault slip, although we cannot exclude this possibility. Some SSAF ruptures do not trigger discernible slip on the NF, rendering such events undetectable in the stratigraphic record. Our research contributes toward discussions regarding the seismic hazard in southern California, shedding light on the interplay between the SSAF and NF.</span></p>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2023JB028621","usgsCitation":"Flores, L., Kyriakopoulos, C., Oglesby, D., Meltzner, A., Rockwell, T., Fletcher, J., and Brothers, D., 2024, Exploring the dynamic interactions between the Southern San Andreas Fault and a normal fault under the Salton Sea: Journal of Geophysical Research Solid Earth, v. 129, no. 11, e2023JB028621, 27 p., https://doi.org/10.1029/2023JB028621.","productDescription":"e2023JB028621, 27 p.","ipdsId":"IP-167490","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":481545,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Salton Sea, Southern San Andreas Fault","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -116.65460420209196,\n              33.84881697934365\n            ],\n            [\n              -115.60752481012484,\n              32.705792541668316\n            ],\n            [\n              -115.09341127848316,\n              32.71621614794114\n            ],\n            [\n              -116.0942650348575,\n              33.93798453809697\n            ],\n            [\n              -116.65460420209196,\n              33.84881697934365\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"129","issue":"11","noUsgsAuthors":false,"publicationDate":"2024-11-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Flores, Luis Ivan Bazan","contributorId":350339,"corporation":false,"usgs":false,"family":"Flores","given":"Luis Ivan Bazan","affiliations":[{"id":17864,"text":"University of Memphis","active":true,"usgs":false}],"preferred":false,"id":925784,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kyriakopoulos, Christodoulos","contributorId":350340,"corporation":false,"usgs":false,"family":"Kyriakopoulos","given":"Christodoulos","affiliations":[{"id":17864,"text":"University of Memphis","active":true,"usgs":false}],"preferred":false,"id":925785,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Oglesby, David D.","contributorId":350341,"corporation":false,"usgs":false,"family":"Oglesby","given":"David D.","affiliations":[{"id":12655,"text":"University of California, Riverside","active":true,"usgs":false}],"preferred":false,"id":925786,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Meltzner, Aron J.","contributorId":350342,"corporation":false,"usgs":false,"family":"Meltzner","given":"Aron J.","affiliations":[{"id":16631,"text":"Nanyang Technological University","active":true,"usgs":false}],"preferred":false,"id":925787,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rockwell, Thomas K.","contributorId":350343,"corporation":false,"usgs":false,"family":"Rockwell","given":"Thomas K.","affiliations":[{"id":6608,"text":"San Diego State University","active":true,"usgs":false}],"preferred":false,"id":925788,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Fletcher, John M.","contributorId":350344,"corporation":false,"usgs":false,"family":"Fletcher","given":"John M.","affiliations":[{"id":82505,"text":"Centro de Investigación Científica y de Educación Superior de Ensenada","active":true,"usgs":false}],"preferred":false,"id":925789,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Brothers, Daniel S. 0000-0001-7702-157X","orcid":"https://orcid.org/0000-0001-7702-157X","contributorId":210199,"corporation":false,"usgs":true,"family":"Brothers","given":"Daniel S.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":925790,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70260170,"text":"sim3521 - 2024 - Geologic map of the southern Stillwater Range, Nevada","interactions":[],"lastModifiedDate":"2025-07-23T16:57:56.517005","indexId":"sim3521","displayToPublicDate":"2024-11-01T14:25:00","publicationYear":"2024","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":"3521","displayTitle":"Geologic Map of the Southern Stillwater Range, Nevada","title":"Geologic map of the southern Stillwater Range, Nevada","docAbstract":"<p>The southern Stillwater Range in west-central Nevada contains the western part of the Oligocene Stillwater-Clan Alpine caldera complex, which extends about 55 kilometers (km) east from the west side of the Stillwater Range to the northwestern Desatoya Mountains. The complex consists of at least seven nested ignimbrite calderas and subjacent plutonic rocks emplaced into a complex basement composed of Mesozoic metasedimentary and metavolcanic rocks and Cretaceous granitic plutons. The calderas formed during large-volume (100s to greater than (&gt;) 2,500 cubic kilometers [km<sup>3</sup>]) eruptions of silicic ignimbrites between about 30.4 and 25.1 million years before present (Ma). The Job Canyon and Poco Canyon calderas and the western part of the much larger Elevenmile Canyon caldera, and their plutonic roots, are exposed in the southern Stillwater Range. There, the caldera complex was steeply tilted during large-magnitude crustal extension in the middle Miocene, and further exhumed during the late Miocene to Holocene Basin and Range extension that formed the modern Stillwater Range. This tilted crustal section affords an exceptional opportunity to view structural cross sections of ignimbrite calderas and their plutonic roots to paleodepths as much as 9–10 km.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/sim3521","collaboration":"Prepared in cooperation with the Nevada Bureau of Mines and Geology","programNote":"National Cooperative Geologic Mapping Program","usgsCitation":"John, D.A., Colgan, J.P., Berry, M.E., Henry, C.D., and Silberling, N.J., 2024, Geologic map of the southern Stillwater Range, Nevada: U.S. Geological Survey Scientific Investigations Map 3521, 2 sheets, scale 1:24,000, 39-p. pamphlet, https://doi.org/10.3133/sim3521.","productDescription":"Report: iv, 39 p.; 3 Sheets: 42.23 x 64.92 inches or smaller; 2 Data Releases","ipdsId":"IP-123012","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":463560,"rank":9,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sim/3521/sim3521.xml"},{"id":463559,"rank":8,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sim/3521/images"},{"id":463384,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7P26X2V","text":"USGS data release","linkHelpText":"Geochemical and geochronologic data from the Stillwater Range, Clan Alpine, and Desatoya Mountains, Nevada (ver. 3.0, December 2023)"},{"id":463383,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9WW1EUF","text":"USGS data release","linkHelpText":"Digital database of the geologic map of the southern Stillwater Range, Nevada"},{"id":463382,"rank":5,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3521/sim3521_sheet2.pdf","text":"Sheet 2—Correlation and list of map units and explanation of map symbols","size":"524 KB","linkFileType":{"id":1,"text":"pdf"},"description":"Sheet 2"},{"id":463381,"rank":4,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3521/sim3521_sheet1-geospatial.pdf","text":"Sheet 1— Georeferenced geologic map","size":"16.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3521 sheet 1 geospatial"},{"id":463380,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3521/sim3521_sheet1.pdf","text":"Sheet 1—Geologic map","size":"15.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3521 sheet 1"},{"id":463379,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3521/sim3521_pamphlet.pdf","text":"Pamphlet","size":"2.74 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3521 pamphlet"},{"id":483247,"rank":10,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sim/3521/versionHist.txt","text":"Version History","size":"4.0 KB","linkFileType":{"id":2,"text":"txt"},"description":"SIM 3521 version history"},{"id":463378,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3521/coverthb2.jpg"},{"id":492781,"rank":11,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_117751.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Nevada","otherGeospatial":"Southern Stillwater Range","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -118.5,\n              39.75\n            ],\n            [\n              -118.5,\n              39.375\n            ],\n            [\n              -118,\n              39.375\n            ],\n            [\n              -118,\n              39.75\n            ],\n            [\n              -118.5,\n              39.75\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","edition":"Version 1.0: November 1, 2024; Version 1.1: March 12, 2025","contact":"<p>Director, <a href=\"https://www.usgs.gov/centers/geosciences-and-environmental-change-science-center/science/\" data-mce-href=\"https://www.usgs.gov/centers/geosciences-and-environmental-change-science-center/science/\">Geosciences and Environmental Change Science Center</a><br>U.S. Geological Survey<br>Box 25046, MS-980<br>Denver, CO 80225-0046</p>","tableOfContents":"<ul><li>Introduction</li><li>Methods</li><li>Stratigraphy</li><li>Description of Map Units</li><li>References Cited</li></ul>","publishedDate":"2024-11-01","revisedDate":"2025-03-12","noUsgsAuthors":false,"publicationDate":"2024-11-01","publicationStatus":"PW","contributors":{"authors":[{"text":"John, David A. 0000-0001-7977-9106 djohn@usgs.gov","orcid":"https://orcid.org/0000-0001-7977-9106","contributorId":1748,"corporation":false,"usgs":true,"family":"John","given":"David","email":"djohn@usgs.gov","middleInitial":"A.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":917299,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Colgan, Joseph P. 0000-0001-6671-1436 jcolgan@usgs.gov","orcid":"https://orcid.org/0000-0001-6671-1436","contributorId":1649,"corporation":false,"usgs":true,"family":"Colgan","given":"Joseph","email":"jcolgan@usgs.gov","middleInitial":"P.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":917300,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Berry, Margaret E. 0000-0002-4113-8212","orcid":"https://orcid.org/0000-0002-4113-8212","contributorId":201560,"corporation":false,"usgs":true,"family":"Berry","given":"Margaret E.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":917301,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Henry, Christopher D.","contributorId":175501,"corporation":false,"usgs":false,"family":"Henry","given":"Christopher D.","affiliations":[{"id":6689,"text":"Nevada Bureau of Mines and Geology","active":true,"usgs":false}],"preferred":false,"id":917302,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Silberling, Norman J.","contributorId":345701,"corporation":false,"usgs":false,"family":"Silberling","given":"Norman","email":"","middleInitial":"J.","affiliations":[{"id":34135,"text":"USGS (deceased)","active":true,"usgs":false}],"preferred":false,"id":917303,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70261872,"text":"70261872 - 2024 - Effect of invasive plant removal on the density of Peromyscus sonoriensis (western deer mice) in Point Reyes National Seashore, California, USA.","interactions":[],"lastModifiedDate":"2025-01-02T14:22:50.155687","indexId":"70261872","displayToPublicDate":"2024-11-01T10:11:30","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1462,"text":"Ecological Restoration","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Effect of invasive plant removal on the density of <i>Peromyscus sonoriensis </i> (western deer mice) in Point Reyes National Seashore, California, USA.","title":"Effect of invasive plant removal on the density of Peromyscus sonoriensis (western deer mice) in Point Reyes National Seashore, California, USA.","docAbstract":"<p>Non-native plants can affect communities through direct competition, and by providing refuge to seed predators, creating apparent competition with native plants. <i>Ammophila arenaria</i> (European beachgrass) has been introduced to coastal dune habitats throughout the western United States where it forms dense monocultures, stabilizes dunes, and alters abiotic and biotic conditions. The dominance of European beachgrass has been linked to declines of<i> Lupinus tidestromii</i> (Tidestrom’s lupine), an herb endemic to coastal dune communities in central and northern California. <i>Peromyscus sonoriensis</i> (western deer mice), a native seed predator, use beachgrass as refuge from predators. Tidestrom’s lupine plants near European beachgrass stands experience greater predation pressure from deer mice. At Point Reyes National Seashore, California, USA (PRNS), mechanical removal, manual pulling, and herbicide treatment have been used to reduce the density of European beachgrass near Tidestrom’s lupine populations. We trapped deer mice at five sites in PRNS that experienced different management regimes and used spatially-explicit capture-recapture models to estimate deer mouse density as a function of site and habitat treatment. We found that deer mouse density was lowest in areas where European beachgrass was mechanically removed and in herbicide-treated foredunes, and highest in areas highly invaded by European beachgrass and <i>Carpobrotus spp.</i> (iceplant). The density of deer mice increased from 2021 to 2022 at every site except one that underwent extensive mechanical removal of European beachgrass from 2010-2011. This study shows enduring effects of European beachgrass removal on the density of a native seed predator and highlights the importance of habitat management for conservation of Tidestrom’s lupine.</p>","language":"English","publisher":"University of Wisconsin Press","doi":"10.3368/er.42.4.271","usgsCitation":"Rose, J.P., Parsons, L., Kleeman, P.M., and Halstead, B., 2024, Effect of invasive plant removal on the density of Peromyscus sonoriensis (western deer mice) in Point Reyes National Seashore, California, USA.: Ecological Restoration, v. 42, no. 4, p. 271-283, https://doi.org/10.3368/er.42.4.271.","productDescription":"14 p.","startPage":"271","endPage":"283","ipdsId":"IP-157736","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":498258,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3368/er.42.4.271","text":"Publisher Index Page"},{"id":465573,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Point Reyes National Seashore","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -123.13596190950221,\n              38.24285655590538\n            ],\n            [\n              -123.13596190950221,\n              37.89014364527141\n            ],\n            [\n              -122.65921084771676,\n              37.89014364527141\n            ],\n            [\n              -122.65921084771676,\n              38.24285655590538\n            ],\n            [\n              -123.13596190950221,\n              38.24285655590538\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"42","issue":"4","noUsgsAuthors":false,"publicationDate":"2024-12-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Rose, Jonathan P. 0000-0003-0874-9166 jprose@usgs.gov","orcid":"https://orcid.org/0000-0003-0874-9166","contributorId":199339,"corporation":false,"usgs":true,"family":"Rose","given":"Jonathan","email":"jprose@usgs.gov","middleInitial":"P.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":922103,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Parsons, Lorraine S 0000-0003-1943-037X","orcid":"https://orcid.org/0000-0003-1943-037X","contributorId":333962,"corporation":false,"usgs":false,"family":"Parsons","given":"Lorraine S","affiliations":[{"id":80025,"text":"NPS - Point Reyes National Seashore - PORE","active":true,"usgs":false}],"preferred":false,"id":922104,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kleeman, Patrick M. 0000-0001-6567-3239 pkleeman@usgs.gov","orcid":"https://orcid.org/0000-0001-6567-3239","contributorId":3948,"corporation":false,"usgs":true,"family":"Kleeman","given":"Patrick","email":"pkleeman@usgs.gov","middleInitial":"M.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":922105,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Halstead, Brian J. 0000-0002-5535-6528 bhalstead@usgs.gov","orcid":"https://orcid.org/0000-0002-5535-6528","contributorId":3051,"corporation":false,"usgs":true,"family":"Halstead","given":"Brian J.","email":"bhalstead@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":922106,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70260412,"text":"sim3527 - 2024 - Geomorphic map of the Umatilla River corridor, Oregon","interactions":[],"lastModifiedDate":"2025-12-22T20:27:56.574752","indexId":"sim3527","displayToPublicDate":"2024-11-01T10:05:11","publicationYear":"2024","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":"3527","title":"Geomorphic map of the Umatilla River corridor, Oregon","docAbstract":"<p><span>This map portrays the distribution of landforms along the Umatilla River in northeastern Oregon and covers a corridor 127 kilometers long from the confluence of the Umatilla River with the Columbia River upstream to Meacham Creek. The map encompasses the valley bottom and extends about 1 kilometer up the adjoining hillslopes. Map data are intended to support water quality and fisheries enhancement efforts pursuant to the First Foods, a resource-management approach that focuses on traditionally gathered foods including water, fish, big game, roots, and berries and calls attention to the reciprocity between people and the foods upon which humans depend.</span></p><p><span>The Umatilla River drains about 6,300 square kilometers on the northwest slope of the Blue Mountains in northeast Oregon. Most of the drainage basin is underlain by Miocene basalt flows of the Columbia River Basalt Group. Younger, weakly lithified, late Miocene and early Pliocene gravel deposits of local origin (for example, McKay Formation) are mapped in a few places. Upland surfaces are mantled with windborne silt (loess) correlative with deposits elsewhere known as the Palouse Formation. Surfaces below an elevation of about 340 meters were inundated repeatedly by large Pleistocene glacial outburst floods, most emanating from glacial Lake Missoula in western Montana. In backflooded areas such as the lower Umatilla River valley, Missoula floods deposited extensive slack-water silt.</span></p><p><span>Areas mapped as open water, active channel and tie channel, flood basin, valley bottom, and modified land constitute the geomorphic floodplain: the area subject to occasional inundation by the Umatilla River. Deposits and landforms within the floodplain are inset into Missoula flood deposits and hence postdate the 20–15-kilo-annum Missoula floods. Some floodplain deposits are no more than a few centuries old, as indicated by substantial erosion and deposition during the Umatilla River flood of February 2020, the largest since systematic measurements began in October 1903. Deposits and landforms of the floodplain are transient features within the longer-term incision of the Umatilla River into mid-Miocene flood basalts and younger gravel of the McKay Formation.</span></p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3527","collaboration":"Prepared in cooperation with the Confederated Tribes of the Umatilla Indian Reservation","usgsCitation":"Yuh, I.P., Haugerud, R.A., O'Connor, J.E., and O'Daniel, S.J., 2024, Geomorphic map of the Umatilla River corridor, Oregon: U.S. Geological Survey Scientific Investigation Map 3527, scale 1:12,000, 6 sheets, https://doi.org/10.3133/sim3527.","productDescription":"6 Sheets: 60.00 x 22.00 inches or smaller; Data Release","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-158910","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":497889,"rank":9,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_117653.htm","linkFileType":{"id":5,"text":"html"}},{"id":463503,"rank":8,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P13OOE7Q","description":"Yuh, I.P., Haugerud, R.A., O’Connor, J.E., and O’Daniel, S.J., 2024, Geospatial database for the geomorphic map of the Umatilla River corridor, Oregon: U.S. Geological Survey data release, https://doi.org/10.5066/P13OOE7Q.","linkHelpText":"Geospatial database for the geomorphic map of the Umatilla River corridor, Oregon"},{"id":463502,"rank":7,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3527/sim3527_sheet06.pdf","text":"Sheet 6","size":"14 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":463501,"rank":6,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3527/sim3527_sheet05.pdf","text":"Sheet 5","size":"14 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":463500,"rank":5,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3527/sim3527_sheet04.pdf","text":"Sheet 4","size":"17 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":463499,"rank":4,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3527/sim3527_sheet03.pdf","text":"Sheet 3","size":"15 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":463498,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3527/sim3527_sheet02.pdf","text":"Sheet 2","size":"13 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":463497,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3527/sim3527_sheet01.pdf","text":"Sheet 1","size":"11 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":463496,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3527/covrthb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"Umatilla River corridor","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -118.33321833933547,\n              45.68071824192785\n            ],\n            [\n              -118.3561230993523,\n              45.730645505488894\n            ],\n            [\n              -118.68247351832258,\n              45.7153349524672\n            ],\n            [\n              -118.92979975453633,\n              45.69914300966221\n            ],\n            [\n              -119.0766497072885,\n              45.72208021102742\n            ],\n            [\n              -119.23122860492205,\n              45.82720081569687\n            ],\n            [\n              -119.31238252617953,\n              45.9495910938214\n            ],\n            [\n              -119.37228184901241,\n              45.932123278858995\n            ],\n            [\n              -119.33556936082459,\n              45.81912165021458\n            ],\n            [\n              -119.34329830570641,\n              45.7652305840443\n            ],\n            [\n              -119.05732734508436,\n              45.64513599220672\n            ],\n            [\n              -118.76555967580092,\n              45.630274925778025\n            ],\n            [\n              -118.33238843274466,\n              45.66767113997548\n            ],\n            [\n              -118.33321833933547,\n              45.68071824192785\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","contact":"<p><a data-mce-href=\"https://www.usgs.gov/centers/gmeg\" href=\"https://www.usgs.gov/centers/gmeg\" target=\"_blank\" rel=\"noopener\">Geology, Minerals, Energy, &amp; Geophysics Science Center</a><br><a data-mce-href=\"https://www.usgs.gov/\" href=\"https://www.usgs.gov/\" target=\"_blank\" rel=\"noopener\">U.S. Geological Survey</a><br>350 N. Akron Rd.<br>Moffett Field, CA 94035</p>","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"publishedDate":"2024-11-01","noUsgsAuthors":false,"publicationDate":"2024-11-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Yuh, Ian P. 0000-0002-0992-2314","orcid":"https://orcid.org/0000-0002-0992-2314","contributorId":295783,"corporation":false,"usgs":true,"family":"Yuh","given":"Ian","email":"","middleInitial":"P.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":917592,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Haugerud, Ralph A. 0000-0001-7302-4351","orcid":"https://orcid.org/0000-0001-7302-4351","contributorId":204669,"corporation":false,"usgs":true,"family":"Haugerud","given":"Ralph","email":"","middleInitial":"A.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":917593,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"O'Connor, Jim E. 0000-0002-7928-5883 oconnor@usgs.gov","orcid":"https://orcid.org/0000-0002-7928-5883","contributorId":140771,"corporation":false,"usgs":true,"family":"O'Connor","given":"Jim E.","email":"oconnor@usgs.gov","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":false,"id":917594,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"O’Daniel, Scott J.","contributorId":140123,"corporation":false,"usgs":false,"family":"O’Daniel","given":"Scott","email":"","middleInitial":"J.","affiliations":[{"id":13390,"text":"Confederated Tribes of the Umatilla Indian Reservation, Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":917595,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70266578,"text":"70266578 - 2024 - Developing a predictive model to identify Sea Lamprey parasitism on Lake Trout using biologgers","interactions":[],"lastModifiedDate":"2025-05-09T14:36:58.886325","indexId":"70266578","displayToPublicDate":"2024-11-01T09:34:10","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":13429,"text":"Transactions of American Fisheries Society","active":true,"publicationSubtype":{"id":10}},"title":"Developing a predictive model to identify Sea Lamprey parasitism on Lake Trout using biologgers","docAbstract":"<div class=\" sec\"><div class=\"title\">Objective</div><p class=\"chapter-para\">Sea Lamprey Petromyzon marinus remain problematic for Lake Trout Salvelinus namaycush restoration in the Laurentian Great Lakes. Fisheries assessments would benefit from knowledge of spatial–temporal patterns of Sea Lamprey parasitism on Lake Trout; however, such patterns are challenging to estimate from wounding rates on caught Lake Trout. Electronic tags have been used to identify distinct fish behaviors (e.g., foraging or spawning) using measurements of acceleration or heart rate. We hypothesized that Sea Lamprey attachment would elicit changes in the heart rate and swimming behavior of Lake Trout. Here, we determined whether tagging devices could record these changes and whether we could accurately predict lamprey attachment on Lake Trout using these recordings.</p></div><div class=\" sec\"><div class=\"title\">Methods</div><p class=\"chapter-para\">Adult Lake Trout (n = 34) were implanted with acceleration and heart rate tags and then were subjected to Sea Lamprey parasitism within a laboratory setting. Approximately 70 different acceleration and heart rate metrics were collected and tried as predictors of lamprey attachment. The top variables were used to train random forest models and then tried on test data sets. The accuracy of these models was then validated using a jackknife approach.</p></div><div class=\" sec\"><div class=\"title\">Result</div><p class=\"chapter-para\">Metrics related to body orientation and heart rate were identified as the best predictors of Sea Lamprey attachment. The best models predicted lamprey attachments with high accuracy; however, individual‐level jackknife tests resulted in less accurate cross‐individual prediction and regularly predicted false negatives. These findings may be related to individual variance in the Lake Trout response to attachment, but there was evidence that the shifting of tags after implantation impacted predictive performance, which could be remedied with adjustments during implantation.</p></div><div class=\" sec\"><div class=\"title\">Conclusions</div><p class=\"chapter-para\">Our study highlights the potential to use tagging devices for quantifying Sea Lamprey attachments on Lake Trout in the wild. Further development appears necessary; however, once improved, these predictive models have the potential to generate field‐based estimates of Sea Lamprey attack rates on Lake Trout.</p></div>","language":"English","publisher":"Oxford Academic","doi":"10.1002/tafs.10491","usgsCitation":"Reeve, C., Adams, J., Miehls, S.M., Lowe, M.R., Cooke, S.J., Moser, M.L., and Brownscombe, J., 2024, Developing a predictive model to identify Sea Lamprey parasitism on Lake Trout using biologgers: Transactions of American Fisheries Society, v. 153, no. 6, p. 781-801, https://doi.org/10.1002/tafs.10491.","productDescription":"21 p.","startPage":"781","endPage":"801","ipdsId":"IP-153709","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":488292,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/tafs.10491","text":"Publisher Index Page"},{"id":485642,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"153","issue":"6","noUsgsAuthors":false,"publicationDate":"2024-11-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Reeve, Connor","contributorId":354867,"corporation":false,"usgs":false,"family":"Reeve","given":"Connor","affiliations":[{"id":17786,"text":"Carleton University","active":true,"usgs":false}],"preferred":false,"id":936593,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Adams, Jean V.","contributorId":354868,"corporation":false,"usgs":false,"family":"Adams","given":"Jean V.","affiliations":[{"id":36206,"text":"Retired","active":true,"usgs":false}],"preferred":false,"id":936594,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Miehls, Scott M. 0000-0002-5546-1854 smiehls@usgs.gov","orcid":"https://orcid.org/0000-0002-5546-1854","contributorId":5007,"corporation":false,"usgs":true,"family":"Miehls","given":"Scott","email":"smiehls@usgs.gov","middleInitial":"M.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":936595,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lowe, Michael R. 0000-0002-4645-9429","orcid":"https://orcid.org/0000-0002-4645-9429","contributorId":10539,"corporation":false,"usgs":true,"family":"Lowe","given":"Michael","email":"","middleInitial":"R.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":false,"id":936596,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cooke, Steven J.","contributorId":224158,"corporation":false,"usgs":false,"family":"Cooke","given":"Steven","email":"","middleInitial":"J.","affiliations":[{"id":17786,"text":"Carleton University","active":true,"usgs":false}],"preferred":false,"id":936597,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Moser, Mary L.","contributorId":195100,"corporation":false,"usgs":false,"family":"Moser","given":"Mary","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":936598,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Brownscombe, Jake W.","contributorId":354870,"corporation":false,"usgs":false,"family":"Brownscombe","given":"Jake W.","affiliations":[{"id":17786,"text":"Carleton University","active":true,"usgs":false}],"preferred":false,"id":936599,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70261022,"text":"70261022 - 2024 - Evaluating the sagebrush conservation design through the lens of a sagebrush indicator species","interactions":[],"lastModifiedDate":"2024-11-20T16:28:34.438486","indexId":"70261022","displayToPublicDate":"2024-11-01T09:19:22","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":6002,"text":"Rangeland Ecology & Management","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating the sagebrush conservation design through the lens of a sagebrush indicator species","docAbstract":"<p>Sagebrush ecosystems support a suite of unique species such as the emblematic greater sage-grouse (<i>Centrocercus urophasianus</i>; sage-grouse) but are under increasing pressure from anthropogenic stressors such as annual grass invasion, conifer encroachment, altered wildfire regimes, and land use change. We examined the ability of an ecosystem-based framework for sagebrush conservation, the sagebrush conservation design (SCD) strategy, and the associated model of sagebrush ecological integrity (SEI), to identify and rank priority habitats for sage-grouse, a sagebrush indicator species. We compared sage-grouse population trends from 1996–2021 across the three ranked SEI categories. We then modeled those trends directly as a function of the same landcover predictors underlying SEI, used the median trend estimates to recategorize the sage-grouse’s range, and used spatial correlation methods to compare our sage-grouse performance categories with those of SEI. Finally, we compared the sage-grouse condition categories, predicted by our landcover-based model, to empirical trends derived from population count data. We found that the SCD and SEI were effective tools for identifying and ranking priority habitats for sage-grouse. Population trends were stable in the core areas identified by SEI but declining in the lower (i.e., growth and other) condition categories. As a result, core areas encompassed an increasingly larger share of the total sage-grouse population in a disproportionately smaller area. Our model supports the general functional relationships between landcover and sage-grouse performance suggested by SEI. We found strong spatial congruence between our categories of predicted sage-grouse population performance, the condition categories of SEI, and empirical trends derived from population count data. Our analysis demonstrates that proactive ecosystem-based approaches to the conservation of the sagebrush biome can help optimize the return on limited conservation resources and benefits for sagebrush obligate species and help reduce some of the real and perceived conflicts inherent in single-species management.</p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.rama.2024.08.021","usgsCitation":"Prochazka, B.G., Lundblad, C.G., Doherty, K., O’Neil, S.T., Tull, J.C., Abele, S., Aldridge, C.L., and Coates, P.S., 2024, Evaluating the sagebrush conservation design through the lens of a sagebrush indicator species: Rangeland Ecology & Management, v. 97, p. 146-159, https://doi.org/10.1016/j.rama.2024.08.021.","productDescription":"14 p.","startPage":"146","endPage":"159","ipdsId":"IP-162640","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":466788,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.rama.2024.08.021","text":"Publisher Index Page"},{"id":464350,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, California, Colorado, Idaho, New Mexico, Nevada, Montana, Oregon, Utah, Washington, Wyoming","otherGeospatial":"Great Plains, Intermountain West, Southern Great Basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -120.46461214797594,\n              47.34790601551299\n            ],\n            [\n              -120.46461214797594,\n              35.22486431641359\n            ],\n            [\n              -104.39395814136043,\n              35.22486431641359\n            ],\n            [\n              -104.39395814136043,\n              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0000-0001-7925-9055","orcid":"https://orcid.org/0000-0001-7925-9055","contributorId":346421,"corporation":false,"usgs":true,"family":"Lundblad","given":"Carl","email":"","middleInitial":"Gregory","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":918951,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Doherty, Kevin E.","contributorId":177793,"corporation":false,"usgs":false,"family":"Doherty","given":"Kevin E.","affiliations":[],"preferred":false,"id":918952,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"O’Neil, Shawn T. 0000-0002-0899-5220","orcid":"https://orcid.org/0000-0002-0899-5220","contributorId":206589,"corporation":false,"usgs":true,"family":"O’Neil","given":"Shawn","email":"","middleInitial":"T.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":918953,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Tull, John C. 0000-0002-0680-008X","orcid":"https://orcid.org/0000-0002-0680-008X","contributorId":201650,"corporation":false,"usgs":false,"family":"Tull","given":"John","email":"","middleInitial":"C.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":918954,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Abele, Steve C.","contributorId":300333,"corporation":false,"usgs":false,"family":"Abele","given":"Steve C.","affiliations":[{"id":65086,"text":"U.S. Fish and Wildlife Service, Reno, Nevada, USA","active":true,"usgs":false}],"preferred":false,"id":918955,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Aldridge, Cameron L. 0000-0003-3926-6941 aldridgec@usgs.gov","orcid":"https://orcid.org/0000-0003-3926-6941","contributorId":191773,"corporation":false,"usgs":true,"family":"Aldridge","given":"Cameron","email":"aldridgec@usgs.gov","middleInitial":"L.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":918956,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Coates, Peter S. 0000-0003-2672-9994 pcoates@usgs.gov","orcid":"https://orcid.org/0000-0003-2672-9994","contributorId":3263,"corporation":false,"usgs":true,"family":"Coates","given":"Peter","email":"pcoates@usgs.gov","middleInitial":"S.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":918957,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70261260,"text":"70261260 - 2024 - Apatite and monazite geochemistry record magmatic and metasomatic processes in rare earth element mineralization at Mountain Pass, California","interactions":[],"lastModifiedDate":"2024-12-04T15:32:09.263599","indexId":"70261260","displayToPublicDate":"2024-11-01T08:24:22","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1472,"text":"Economic Geology","active":true,"publicationSubtype":{"id":10}},"title":"Apatite and monazite geochemistry record magmatic and metasomatic processes in rare earth element mineralization at Mountain Pass, California","docAbstract":"The largest rare earth element (REE) deposit in the United States is a carbonatite intrusion at Mountain Pass in the Mojave Desert, California. Despite a clear spatiotemporal association of alkaline silicate and carbonatite intrusions at Mountain Pass, a genetic model of their mutual formation has not been resolved. The Mountain Pass carbonatite has long been upheld as an example of a primary magmatic body, but recent work has suggested it could be fluid-derived. This study investigates the geochemistry of apatite and monazite grains from the alkaline silicate and carbonatite stocks and dikes of the Mountain Pass district, to elucidate the magmatic history of the intrusive suite and identify the role of fluids in rare earth element mineralization. Three apatite populations are identified in the alkaline silicate rocks. A primary magmatic apatite group supports intrusion of the stocks as separate pulses of magma derived from a spatially extensive metasomatized mantle source region. The second group implicates the role of a regional fluid that mobilized light rare earth elements from apatite grains. A minor group of inherited apatite cores, identified by low Sr and negative Eu anomalies, supports assimilation of crustal material in the formation of the intrusive suite. Analyses of monazite and apatite grains from the carbonatite orebody also reveal a mix of primary magmatic and metasomatic (fluid-related) minerals. Compositional similarities between primary phosphates in the carbonatite and alkaline silicate rocks support a genetic link between the intrusive suites. The presence of fluids regionally and within the carbonatite orebody indicates the Mountain Pass carbonatite should not be classified as a purely magmatic REE deposit.","language":"English","publisher":"GeoScienceWorld","doi":"10.5382/econgeo.5108","usgsCitation":"Benson, E.K., and Watts, K., 2024, Apatite and monazite geochemistry record magmatic and metasomatic processes in rare earth element mineralization at Mountain Pass, California: Economic Geology, v. 119, no. 7, p. 1611-1642, https://doi.org/10.5382/econgeo.5108.","productDescription":"32 p.","startPage":"1611","endPage":"1642","ipdsId":"IP-159227","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":466789,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5382/econgeo.5108","text":"Publisher Index Page"},{"id":464750,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, California, Nevada","otherGeospatial":"Mojave Desert, Mountain Pass","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -114.06188935809527,\n              36.65925978640696\n            ],\n            [\n              -115.95168822883412,\n              36.65925978640696\n            ],\n            [\n              -115.95168822883412,\n              34.494804652285\n            ],\n            [\n              -114.06188935809527,\n              34.494804652285\n            ],\n            [\n              -114.06188935809527,\n              36.65925978640696\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"119","issue":"7","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Benson, Erin Kay 0000-0003-3166-6043","orcid":"https://orcid.org/0000-0003-3166-6043","contributorId":346098,"corporation":false,"usgs":true,"family":"Benson","given":"Erin","email":"","middleInitial":"Kay","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":920137,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Watts, Kathryn E. 0000-0002-6110-7499","orcid":"https://orcid.org/0000-0002-6110-7499","contributorId":204344,"corporation":false,"usgs":true,"family":"Watts","given":"Kathryn E.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":920138,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70266842,"text":"70266842 - 2024 - Juvenile coho salmon growth differences track biennial pink salmon spawning patterns","interactions":[],"lastModifiedDate":"2025-05-13T15:33:11.662904","indexId":"70266842","displayToPublicDate":"2024-11-01T00:00:00","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1696,"text":"Freshwater Biology","active":true,"publicationSubtype":{"id":10}},"title":"Juvenile coho salmon growth differences track biennial pink salmon spawning patterns","docAbstract":"<p>1. Spawning Pacific salmon (<i>Oncorhynchus</i>&nbsp;spp.) provide marine-derived resources (MDR) to freshwater food webs in the form of eggs, flesh and maggots that consume salmon carcasses, all of which positively impact stream-dwelling fish growth. Pink salmon (<i>O. gorbuscha</i>) are widely distributed throughout coastal catchments along the North Pacific Ocean and display increased spawning abundances in odd years, owing to a fixed 2-year life history. While many studies have found that foraging and growth of stream-dwelling salmonids are improved by increased adult salmon spawning abundance, few studies have investigated the importance of alternating pink salmon spawning abundance between years.</p><p>2. Here, we examined how patterns of pink salmon spawning abundance impact the foraging and growth of juvenile coho salmon (<i>O. kisutch</i>). First, we used bioenergetic simulations to generate a hypothesis that coho salmon growth would increase during odd relative to even years. We then collected empirical juvenile coho salmon diet and growth data from a Southeast Alaska catchment in 2021 (pink salmon spawning) and 2022 (no pink salmon spawning). Field data were compared against simulation predictions to understand impacts of biennial pink salmon spawning patterns on juvenile coho salmon growth.</p><p>3. Empirical growth data revealed similar patterns to bioenergetic simulations. Age-1 coho salmon grew 16.6 mm longer and 5.5 g heavier on average in 2021 compared to 2022. Age-0 coho salmon displayed minor growth differences between years.</p><p>4. These results support bioenergetic model predictions and suggest that patterns of pink salmon spawning abundance can impart interannual growth disparities to juvenile coho salmon. Moreover, we show that distinct spawning characteristics of Pacific salmon species are important when understanding patterns of MDR transfer and growth responses in stream fishes.</p>","language":"English","publisher":"Wiley","doi":"10.1111/fwb.14328","usgsCitation":"Fitzgerald, K., Bellmore, J., Fellman, J., Cheng, M., Boyles-Muehleck, N., Delbecq, C., and Falke, J.A., 2024, Juvenile coho salmon growth differences track biennial pink salmon spawning patterns: Freshwater Biology, v. 69, no. 11, p. 1583-1595, https://doi.org/10.1111/fwb.14328.","productDescription":"13 p.","startPage":"1583","endPage":"1595","ipdsId":"IP-155328","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":485820,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","city":"Juneau","otherGeospatial":"Tongass National Forest, upper Montana Creek","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -134.02770952221633,\n              58.39172878863832\n            ],\n            [\n              -134.02770952221633,\n              57.6331041033996\n            ],\n            [\n              -133.0242790552512,\n              57.6331041033996\n            ],\n            [\n              -133.0242790552512,\n              58.39172878863832\n            ],\n            [\n              -134.02770952221633,\n              58.39172878863832\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"69","issue":"11","noUsgsAuthors":false,"publicationDate":"2024-09-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Fitzgerald, Kevin A.","contributorId":355111,"corporation":false,"usgs":false,"family":"Fitzgerald","given":"Kevin A.","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":936879,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bellmore, J. Ryan","contributorId":355112,"corporation":false,"usgs":false,"family":"Bellmore","given":"J. Ryan","affiliations":[{"id":40821,"text":"U. S. Department of Agriculture","active":true,"usgs":false}],"preferred":false,"id":936880,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fellman, Jason B.","contributorId":355113,"corporation":false,"usgs":false,"family":"Fellman","given":"Jason B.","affiliations":[{"id":84706,"text":"University of Alaska Southeast,  Forest Service","active":true,"usgs":false}],"preferred":false,"id":936881,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cheng, Matthew L.H.","contributorId":355115,"corporation":false,"usgs":false,"family":"Cheng","given":"Matthew L.H.","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":936882,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Boyles-Muehleck, Naomi","contributorId":355118,"corporation":false,"usgs":false,"family":"Boyles-Muehleck","given":"Naomi","affiliations":[{"id":16298,"text":"University of Alaska Southeast","active":true,"usgs":false}],"preferred":false,"id":936883,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Delbecq, Claire E.","contributorId":355120,"corporation":false,"usgs":false,"family":"Delbecq","given":"Claire E.","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":936884,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Falke, Jeffrey A. 0000-0002-6670-8250 jfalke@usgs.gov","orcid":"https://orcid.org/0000-0002-6670-8250","contributorId":5195,"corporation":false,"usgs":true,"family":"Falke","given":"Jeffrey","email":"jfalke@usgs.gov","middleInitial":"A.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":936885,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70260921,"text":"70260921 - 2024 - Best practices for incorporating climate change science into Department of the Interior analyses, consultations, and decision making","interactions":[],"lastModifiedDate":"2024-11-15T14:01:02.523252","indexId":"70260921","displayToPublicDate":"2024-10-31T09:00:00","publicationYear":"2024","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"title":"Best practices for incorporating climate change science into Department of the Interior analyses, consultations, and decision making","docAbstract":"<p>The purpose of this document is to provide technical guidance, practical application examples, and resource lists for those who conduct, manage, and/or interpret technical workflows within the Department of the Interior. This document is intended to support implementation of Department of the Interior policy 526 DM 1 and establish best practices for using climate change science to inform analysis, consultation, and decision making.</p><p>The Earth’s climate is an interconnected system that distributes energy, heat, and water around the planet. Due to human-driven increases in long-lived greenhouse gases, the Earth’s climate is now changing. For Departmental decision-making purposes, assuming a static, unchanging baseline climate is no longer consistent with current knowledge about the climate system.</p><p>There are uncertainties about future climate and how resources or assets (RoAs) will respond to new conditions. To depict the possibilities, the global climate science community develops scenarios and models to explore how future climate may respond to socioeconomic and technological development in the world.</p><p>Principles for informing policy development, planning and decisions, and regulatory processes using climate change science must: 1) consider the effects of future climate change, 2) characterize the risks, and 3) characterize the uncertainties.</p><p>Best practices include:</p><p><strong>Use multiple scenarios</strong> to assess risks from a range of plausible societal pathways. When constraints prevent the use of multiple scenarios or if decision makers are risk averse, ensure that the chosen scenario considers higher risk outcomes. This is particularly important for large investments or irreversible decisions and reduces the chances of overconfident decision making.</p><p><strong>Use multiple climate models within each scenario</strong> to account for the range of outcomes due to model uncertainty. Do not rely solely on a single model or an ensemble average.</p><p><strong>Use relevant climate data</strong>. Use a time-period for model projections of the future climate change consistent with the relevant timeframe of the policy, action, or decision being considered. Historical observations are useful for understanding past conditions and climate trends for the next several years, but not beyond the next decade. Consult with climate data and modeling experts to assess which data and model resources are most appropriate for any given application.</p><p><strong>Clearly describe key analysis uncertainties</strong> (including with any climate observations, models, and scenarios used), <strong>and how they were addressed</strong> in the analysis and/or decision process. This ensures transparency and learning among analysts and decision makers.</p>","language":"English","publisher":"Department of the Interior","doi":"10.21429/hjgj-j073","usgsCitation":"Terando, A.J., Tucker, A.M., Runyon, A.N., Miller, J., Perkins, J.L., Kimbrel, S.W., Cross, A.S., and Boyles, R.P., 2024, Best practices for incorporating climate change science into Department of the Interior analyses, consultations, and decision making, iv, 72 p., https://doi.org/10.21429/hjgj-j073.","productDescription":"iv, 72 p.","ipdsId":"IP-166512","costCenters":[],"links":[{"id":464070,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/unnumbered/70260921/coverthb.jpg"},{"id":464071,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/unnumbered/70260921/70260921.pdf","linkFileType":{"id":1,"text":"pdf"}}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Terando, Adam J. 0000-0002-9280-043X aterando@usgs.gov","orcid":"https://orcid.org/0000-0002-9280-043X","contributorId":173447,"corporation":false,"usgs":true,"family":"Terando","given":"Adam","email":"aterando@usgs.gov","middleInitial":"J.","affiliations":[{"id":565,"text":"Southeast Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":918516,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tucker, Anna Maureen 0000-0002-1473-2048 amtucker@usgs.gov","orcid":"https://orcid.org/0000-0002-1473-2048","contributorId":257906,"corporation":false,"usgs":true,"family":"Tucker","given":"Anna","email":"amtucker@usgs.gov","middleInitial":"Maureen","affiliations":[],"preferred":true,"id":918517,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Runyon, Amber N. 0000-0002-7282-1217","orcid":"https://orcid.org/0000-0002-7282-1217","contributorId":346252,"corporation":false,"usgs":false,"family":"Runyon","given":"Amber","email":"","middleInitial":"N.","affiliations":[{"id":36976,"text":"U.S. National Park Service","active":true,"usgs":false}],"preferred":false,"id":918518,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Miller, James A.","contributorId":346253,"corporation":false,"usgs":false,"family":"Miller","given":"James A.","affiliations":[{"id":7217,"text":"Bureau of Land Management","active":true,"usgs":false}],"preferred":false,"id":918519,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Perkins, Judy L.","contributorId":266176,"corporation":false,"usgs":false,"family":"Perkins","given":"Judy","email":"","middleInitial":"L.","affiliations":[{"id":54938,"text":"U.S. Bureau of Land Management, California State Office, 2800 Cottage Way, Sacramento, CA 95825","active":true,"usgs":false}],"preferred":false,"id":918520,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kimbrel, Sean W.","contributorId":346255,"corporation":false,"usgs":false,"family":"Kimbrel","given":"Sean","email":"","middleInitial":"W.","affiliations":[{"id":6736,"text":"Bureau of Reclamation","active":true,"usgs":false}],"preferred":false,"id":918521,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Cross, Amanda S.","contributorId":346256,"corporation":false,"usgs":false,"family":"Cross","given":"Amanda","email":"","middleInitial":"S.","affiliations":[{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false}],"preferred":false,"id":918522,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Boyles, Ryan P. 0000-0001-9272-867X rboyles@usgs.gov","orcid":"https://orcid.org/0000-0001-9272-867X","contributorId":197670,"corporation":false,"usgs":true,"family":"Boyles","given":"Ryan","email":"rboyles@usgs.gov","middleInitial":"P.","affiliations":[{"id":36940,"text":"National Climate Adaptation Science Center","active":true,"usgs":true}],"preferred":true,"id":918523,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70260103,"text":"sir20245097 - 2024 - Use of continuous water-quality time-series data to compute total phosphorus concentrations and loads for the Missouri River at St. Joseph and Hermann, Missouri, 2007–22","interactions":[],"lastModifiedDate":"2025-12-22T20:23:35.597848","indexId":"sir20245097","displayToPublicDate":"2024-10-30T10:46:09","publicationYear":"2024","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":"2024-5097","displayTitle":"Use of Continuous Water-Quality Time-Series Data to Compute Total Phosphorus Concentrations and Loads for the Missouri River at St. Joseph and Hermann, Missouri, 2007–22","title":"Use of continuous water-quality time-series data to compute total phosphorus concentrations and loads for the Missouri River at St. Joseph and Hermann, Missouri, 2007–22","docAbstract":"<p>In support of Missouri’s Nutrient Loss Reduction Strategy, which was created to reduce the nutrient contamination of Missouri’s waterways from point and nonpoint sources, total phosphorus concentrations and loads were computed for the Missouri River at St. Joseph, Missouri, streamgage (U.S. Geological Survey station 06818000) and the Missouri River at Hermann, Mo., streamgage (U.S. Geological Survey station 06934500) for October 2007 to September 2022 using surrogate models and continuous turbidity sensor data. To obtain a more complete total phosphorus record for the study period, LOAD ESTimator (LOADEST) regression models using flow were used when turbidity sensor data were unavailable to estimate daily total phosphorus loads. This report presents the methods and results for the computed total phosphorus concentrations, loads, and yields for the two study sites on the Missouri River. With continued data collection and ongoing model evaluation and maintenance, the surrogate models may be useful into the future for computing total phosphorus concentrations and loads.</p><p>Daily mean total phosphorus concentrations calculated using a surrogate model at the Missouri River at St. Joseph, Mo., streamgage during the 15-year study period (water years 2008 through 2022) ranged from 0.104 to 4.56 milligrams per liter (mg/L; median of 0.272 mg/L), and computed total phosphorus daily loads (with gaps in the daily record filled using the LOADEST regression model) ranged from 5.19 to 1,760 tons per day (tons/d; median of 36.5 tons/d). Annual loads ranged from 9,570 tons in water year 2022 to 50,500 tons in water year 2019. The total load for the study period was 437,000 tons.</p><p>For the Missouri River at Hermann, Mo., streamgage during the same 15-year study period, daily mean total phosphorus concentrations, calculated using surrogate models applied to low and high turbidity values, ranged from 0.183 to 1.97 mg/L (median of 0.319 mg/L), and computed total phosphorus daily loads (with gaps in the daily record filled using the LOADEST regression model) ranged from 12.7 to 1,970 tons/d (median of 76.8 tons/d). Annual loads ranged from 22,600 tons in water year 2022 to 101,000 tons in water year 2019. The total load for the study period was 833,000 tons, which is nearly twice that at the Missouri River at St. Joseph, Mo., streamgage.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20245097","collaboration":"Prepared in cooperation with Missouri Department of Natural Resources","usgsCitation":"Markland, K.M., 2024, Use of continuous water-quality time-series data to compute total phosphorus concentrations and loads for the Missouri River at St. Joseph and Hermann, Missouri, 2007–22: U.S. Geological Survey Scientific Investigations Report 2024–5097, 26 p., https://doi.org/10.3133/sir20245097.","productDescription":"Report: vii, 26 p.; Data Release; Dataset","numberOfPages":"38","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-161927","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":463254,"rank":6,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"- USGS water data for the Nation"},{"id":463253,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20245097/full"},{"id":463252,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2024/5097/images/"},{"id":463251,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2024/5097/sir20245097.XML"},{"id":463250,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2024/5097/sir20245097.pdf","text":"Report","size":"6.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2024–5097"},{"id":463249,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2024/5097/coverthb.jpg"},{"id":497886,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_117740.htm","linkFileType":{"id":5,"text":"html"}},{"id":463255,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P17PHYDZ","text":"USGS data release","linkHelpText":"Data and model archive summaries to support use of continuous water-quality time-series data to compute total phosphorus concentrations and loads for the Missouri River at St. Joseph and Hermann, Missouri, 2007–22"}],"country":"United States","state":"Missouri","city":"Hermann, St. Joseph","otherGeospatial":"Missouri River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -91.48454431267173,\n              38.7389466373896\n            ],\n            [\n              -91.48454431267173,\n              38.678901791033724\n            ],\n            [\n              -91.40123726792416,\n              38.678901791033724\n            ],\n            [\n              -91.40123726792416,\n              38.7389466373896\n            ],\n            [\n              -91.48454431267173,\n              38.7389466373896\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -95.002636709889,\n              39.854445017011784\n            ],\n            [\n              -95.002636709889,\n              39.62967769348404\n            ],\n            [\n              -94.65186218929263,\n              39.62967769348404\n            ],\n            [\n              -94.65186218929263,\n              39.854445017011784\n            ],\n            [\n              -95.002636709889,\n              39.854445017011784\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","contact":"<p>Director, <a href=\"https://www.usgs.gov/centers/cm-water\" data-mce-href=\"https://www.usgs.gov/centers/cm-water\">Central Midwest Water Science Center</a><br>U.S. Geological Survey<br>400 South Clinton Street, Suite 269<br>Iowa City, IA 52240</p><p><a href=\"https://pubs.usgs.gov/contact\" data-mce-href=\"../contact\">Contact Pubs Warehouse</a></p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Methods</li><li>Water-Quality Sample and Sensor Data</li><li>Surrogate Models</li><li>Summary</li><li>References Cited</li><li>Appendix 1. Supplemental Figures</li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2024-10-30","noUsgsAuthors":false,"publicationDate":"2024-10-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Markland, Kendra M. 0000-0002-0276-8684 kmarkland@usgs.gov","orcid":"https://orcid.org/0000-0002-0276-8684","contributorId":306212,"corporation":false,"usgs":true,"family":"Markland","given":"Kendra","email":"kmarkland@usgs.gov","middleInitial":"M.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":916997,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70262024,"text":"70262024 - 2024 - Penguin colony georegistration using camera pose estimation and phototourism","interactions":[],"lastModifiedDate":"2025-01-10T16:30:20.637582","indexId":"70262024","displayToPublicDate":"2024-10-30T10:26:02","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Penguin colony georegistration using camera pose estimation and phototourism","docAbstract":"<p><span>Satellite-based remote sensing and uncrewed aerial imagery play increasingly important roles in the mapping of wildlife populations and wildlife habitat, but the availability of imagery has been limited in remote areas. At the same time, ecotourism is a rapidly growing industry and can yield a vast catalog of photographs that could be harnessed for monitoring purposes, but the inherently ad-hoc and unstructured nature of these images make them difficult to use. To help address this, a subfield of computer vision known as phototourism has been developed to leverage a diverse collection of unstructured photographs to reconstruct a georeferenced three-dimensional scene capturing the environment at that location. Here we demonstrate the use of phototourism in an application involving Antarctic penguins, sentinel species whose dynamics are closely tracked as a measure of ecosystem functioning, and introduce a semi-automated pipeline for aligning and registering ground photographs using a digital elevation model (DEM) and satellite imagery. We employ the Segment Anything Model (SAM) for the interactive identification and segmentation of penguin colonies in these photographs. By creating a textured 3D mesh from the DEM and satellite imagery, we estimate camera poses to align ground photographs with the mesh and register the segmented penguin colony area to the mesh, achieving a detailed representation of the colony. Our approach has demonstrated promising performance, though challenges persist due to variations in image quality and the dynamic nature of natural landscapes. Nevertheless, our method offers a straightforward and effective tool for the georegistration of ad-hoc photographs in natural landscapes, with additional applications such as monitoring glacial retreat.</span></p>","language":"English","publisher":"PLoS","doi":"10.1371/journal.pone.0311038","usgsCitation":"Wu, H., Flynn, C., Hall, C., Che-Castaldo, C., Samaras, D., Schwaller, M., and Lynch, H., 2024, Penguin colony georegistration using camera pose estimation and phototourism: PLoS ONE, v. 19, no. 10, e0311038, 18 p., https://doi.org/10.1371/journal.pone.0311038.","productDescription":"e0311038, 18 p.","ipdsId":"IP-160209","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":466795,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0311038","text":"Publisher Index Page"},{"id":465996,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"19","issue":"10","noUsgsAuthors":false,"publicationDate":"2024-10-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Wu, Haoyu","contributorId":347903,"corporation":false,"usgs":false,"family":"Wu","given":"Haoyu","affiliations":[{"id":36488,"text":"Stony Brook University","active":true,"usgs":false}],"preferred":false,"id":922740,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Flynn, Clare","contributorId":347904,"corporation":false,"usgs":false,"family":"Flynn","given":"Clare","affiliations":[{"id":36488,"text":"Stony Brook University","active":true,"usgs":false}],"preferred":false,"id":922741,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hall, Carole","contributorId":347905,"corporation":false,"usgs":false,"family":"Hall","given":"Carole","affiliations":[{"id":36488,"text":"Stony Brook University","active":true,"usgs":false}],"preferred":false,"id":922742,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Che-Castaldo, Christian Joseph 0000-0002-7670-2178","orcid":"https://orcid.org/0000-0002-7670-2178","contributorId":347906,"corporation":false,"usgs":true,"family":"Che-Castaldo","given":"Christian Joseph","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":922743,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Samaras, Dimitris","contributorId":347907,"corporation":false,"usgs":false,"family":"Samaras","given":"Dimitris","affiliations":[{"id":36488,"text":"Stony Brook University","active":true,"usgs":false}],"preferred":false,"id":922744,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Schwaller, Mathew","contributorId":347909,"corporation":false,"usgs":false,"family":"Schwaller","given":"Mathew","affiliations":[{"id":36488,"text":"Stony Brook University","active":true,"usgs":false}],"preferred":false,"id":922745,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lynch, Heather J.","contributorId":347911,"corporation":false,"usgs":false,"family":"Lynch","given":"Heather J.","affiliations":[{"id":36488,"text":"Stony Brook University","active":true,"usgs":false}],"preferred":false,"id":922746,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70261121,"text":"70261121 - 2024 - Examining inter-regional and intra-seasonal differences in wintering waterfowl landscape associations among Pacific and Atlantic flyways","interactions":[{"subject":{"id":70261121,"text":"70261121 - 2024 - Examining inter-regional and intra-seasonal differences in wintering waterfowl landscape associations among Pacific and Atlantic flyways","indexId":"70261121","publicationYear":"2024","noYear":false,"title":"Examining inter-regional and intra-seasonal differences in wintering waterfowl landscape associations among Pacific and Atlantic flyways"},"predicate":"SUPERSEDED_BY","object":{"id":70261880,"text":"70261880 - 2025 - Examining inter-regional and intra-seasonal differences in wintering waterfowl landscape associations among Pacific and Atlantic flyways","indexId":"70261880","publicationYear":"2025","noYear":false,"title":"Examining inter-regional and intra-seasonal differences in wintering waterfowl landscape associations among Pacific and Atlantic flyways"},"id":1}],"supersededBy":{"id":70261880,"text":"70261880 - 2025 - Examining inter-regional and intra-seasonal differences in wintering waterfowl landscape associations among Pacific and Atlantic flyways","indexId":"70261880","publicationYear":"2025","noYear":false,"title":"Examining inter-regional and intra-seasonal differences in wintering waterfowl landscape associations among Pacific and Atlantic flyways"},"lastModifiedDate":"2025-01-27T17:18:30.964189","indexId":"70261121","displayToPublicDate":"2024-10-30T08:30:41","publicationYear":"2024","noYear":false,"publicationType":{"id":27,"text":"Preprint"},"publicationSubtype":{"id":32,"text":"Preprint"},"seriesTitle":{"id":19836,"text":"Authorea","active":true,"publicationSubtype":{"id":32}},"title":"Examining inter-regional and intra-seasonal differences in wintering waterfowl landscape associations among Pacific and Atlantic flyways","docAbstract":"The Central Valley of California (CVC) and Mid-Atlantic (MA) in the U.S. are both critical sites for nationwide food security (California Poultry Federation 2016, Prosser et al. 2017), and many waterfowl species annually, especially during the winter, providing feeding and roosting locations for a variety of species. Mapping waterfowl distributions, using NEXRAD, may aid in the adaptive management of important waterfowl habitat and allow various government agencies to better understand the interface between wild and domestic birds and commercial agricultural practices. We used 9 years (2014–2023) of data from the US NEXRAD network to model winter waterfowl relative abundance in the CVC and MA as a function of weather, temporal period, environmental conditions, and landcover characteristics using Boosted Regression Tree modelling. We were able to quantify the variability in effect size of 28 different covariates across space and time within two geographic regions which are critical to nationwide waterfowl management and host a high density of nationally important commercial agriculture. In general, weather, geographic (distance to features), and landcover condition (wetness index) predictors had the strongest relative effect on predicting wintering waterfowl relative abundance in both regions, while effects of land cover composition were more regionally and temporally specific. Increased daily mean temperature was a major predictor of increasing relative waterfowl abundance in both regions throughout the winter. Increasing precipitation had differing effects within regions, increasing relative waterfowl abundance in the MA, while decreasing in general within the CVC. Increasing relative waterfowl abundance in the CVC are strongly tied to the flooding of the landscape and rice availability, whereas waterfowl in the MA, where water is less limiting, are generally governed by waste grain availability and emergent wetland on the landscape. Waterfowl relative abundance in the MA was generally higher nearer to the Atlantic coast and lakes, while in the CVC they were higher nearer to lakes. Our findings promote a better understanding of spatial associations of waterfowl to landscape features and may aid in conservation and biosecurity management protocols.","language":"English","publisher":"Authorea","doi":"10.22541/au.173030440.00154170/v1","usgsCitation":"Hardy, M., Williams, C.K., Ladman, B.S., Pitesky, M.E., Overton, C.T., Casazza, M.L., Matchett, E., Prosser, D.J., and Buler, J.J., 2024, Examining inter-regional and intra-seasonal differences in wintering waterfowl landscape associations among Pacific and Atlantic flyways: Authorea, https://doi.org/10.22541/au.173030440.00154170/v1.","productDescription":"51 p.","ipdsId":"IP-172616","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":466797,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.22541/au.173030440.00154170/v1","text":"External Repository"},{"id":466796,"rank":2,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.22541/au.173030440.00154170/v1","text":"External Repository"},{"id":464459,"rank":3,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hardy, Matthew J.","contributorId":343392,"corporation":false,"usgs":false,"family":"Hardy","given":"Matthew J.","affiliations":[{"id":13359,"text":"University of Delaware","active":true,"usgs":false}],"preferred":false,"id":919360,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Williams, Christopher K.","contributorId":202263,"corporation":false,"usgs":false,"family":"Williams","given":"Christopher","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":919361,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ladman, Brian S.","contributorId":337102,"corporation":false,"usgs":false,"family":"Ladman","given":"Brian","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":919362,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pitesky, Maurice E.","contributorId":176920,"corporation":false,"usgs":false,"family":"Pitesky","given":"Maurice","email":"","middleInitial":"E.","affiliations":[{"id":7214,"text":"University of California, Davis","active":true,"usgs":false}],"preferred":false,"id":919363,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Overton, Cory T. 0000-0002-5060-7447 coverton@usgs.gov","orcid":"https://orcid.org/0000-0002-5060-7447","contributorId":3262,"corporation":false,"usgs":true,"family":"Overton","given":"Cory","email":"coverton@usgs.gov","middleInitial":"T.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":919364,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Casazza, Michael L. 0000-0002-5636-735X mike_casazza@usgs.gov","orcid":"https://orcid.org/0000-0002-5636-735X","contributorId":2091,"corporation":false,"usgs":true,"family":"Casazza","given":"Michael","email":"mike_casazza@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":919365,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Matchett, Elliott 0000-0001-5095-2884 ematchett@usgs.gov","orcid":"https://orcid.org/0000-0001-5095-2884","contributorId":5541,"corporation":false,"usgs":true,"family":"Matchett","given":"Elliott","email":"ematchett@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":919366,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Prosser, Diann J. 0000-0002-5251-1799","orcid":"https://orcid.org/0000-0002-5251-1799","contributorId":221167,"corporation":false,"usgs":true,"family":"Prosser","given":"Diann","middleInitial":"J.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":919367,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Buler, Jeffrey J.","contributorId":194648,"corporation":false,"usgs":false,"family":"Buler","given":"Jeffrey","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":919368,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
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