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 (Catostomus latipinnis) 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.
","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":"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 (Mayaheros urophthalmus) and Oscar (Astronotus ocellatus). 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.
","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 Page"},{"id":484504,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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\"}}]}","volume":"39","issue":"1","noUsgsAuthors":false,"publicationDate":"2024-11-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Scott, Alexandra M.","contributorId":353193,"corporation":false,"usgs":false,"family":"Scott","given":"Alexandra M.","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":933153,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":933154,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"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":"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 m of vertical offset since ∼2–3 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.
","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":"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 (>) 2,500 cubic kilometers [km3]) 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.
","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":"Director, Geosciences and Environmental Change Science Center
U.S. Geological Survey
Box 25046, MS-980
Denver, CO 80225-0046
Non-native plants can affect communities through direct competition, and by providing refuge to seed predators, creating apparent competition with native plants. Ammophila arenaria (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 Lupinus tidestromii (Tidestrom’s lupine), an herb endemic to coastal dune communities in central and northern California. Peromyscus sonoriensis (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 Carpobrotus spp. (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.
","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":"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.
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.
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.
","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":"Geology, Minerals, Energy, & Geophysics Science Center
U.S. Geological Survey
350 N. Akron Rd.
Moffett Field, CA 94035
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.
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.
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.
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.
Sagebrush ecosystems support a suite of unique species such as the emblematic greater sage-grouse (Centrocercus urophasianus; 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.
","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 47.34790601551299\n ],\n [\n -120.46461214797594,\n 47.34790601551299\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"97","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Prochazka, Brian G. 0000-0001-7270-5550 bprochazka@usgs.gov","orcid":"https://orcid.org/0000-0001-7270-5550","contributorId":174839,"corporation":false,"usgs":true,"family":"Prochazka","given":"Brian","email":"bprochazka@usgs.gov","middleInitial":"G.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":918950,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lundblad, Carl Gregory 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":"1. Spawning Pacific salmon (Oncorhynchus 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 (O. gorbuscha) 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.
2. Here, we examined how patterns of pink salmon spawning abundance impact the foraging and growth of juvenile coho salmon (O. kisutch). 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.
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.
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.
","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":70274739,"text":"70274739 - 2024 - Heart of the West: Wyoming’s commitment to conservation of migratory ungulates","interactions":[],"lastModifiedDate":"2026-04-09T15:24:19.392049","indexId":"70274739","displayToPublicDate":"2024-10-31T10:18:46","publicationYear":"2024","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Heart of the West: Wyoming’s commitment to conservation of migratory ungulates","docAbstract":"The small town of Superior, Wyoming, used to be a booming coal town. Pictures from the 1920s reveal sparkling new cars, a bowling alley, and other amenities supported by the wealth of the coal mines. Today, those prosperous days are nowhere to be seen. Superior doesn’t have a grocery store or a gas station, and the local bar is only open occasionally. Aside from the low-slung, modest houses built into the hills around town, the most prominent structure is the county road maintenance shop.
But those hills are also dotted with mule deer—lots of them. Superior represents the southern terminus of the world’s longest-recorded mule deer migration. The study of these deer has shaped how wildlife biologists think about migration, and the conservation of their corridor illustrates how science informs the management of iconic Western wildlife populations. These deer, and their story, may also represent what is possible when we recognize the habitat needs of wildlife that move across the same landscapes where we live and work.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"A watershed moment: The American West in the age of limits","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"University of Utah Press","usgsCitation":"Reed, E., and Kauffman, M.J., 2024, Heart of the West: Wyoming’s commitment to conservation of migratory ungulates, chap. of A watershed moment: The American West in the age of limits, p. 248-262.","productDescription":"15 p.","startPage":"248","endPage":"262","ipdsId":"IP-166746","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":502355,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -111.02791442700837,\n 45.00491516402994\n ],\n [\n -111.02791442700837,\n 40.995252415428496\n ],\n [\n -104.0279534875161,\n 40.995252415428496\n ],\n [\n -104.0279534875161,\n 45.00491516402994\n ],\n [\n -111.02791442700837,\n 45.00491516402994\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Reed, Emily","contributorId":299809,"corporation":false,"usgs":false,"family":"Reed","given":"Emily","affiliations":[{"id":63974,"text":"Wyoming Cooperative Fish and Wildlife Research Unit","active":true,"usgs":false}],"preferred":false,"id":958899,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kauffman, Matthew J. 0000-0003-0127-3900","orcid":"https://orcid.org/0000-0003-0127-3900","contributorId":210786,"corporation":false,"usgs":true,"family":"Kauffman","given":"Matthew","middleInitial":"J.","affiliations":[{"id":484,"text":"Northwest Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":958900,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"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":"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.
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.
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.
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.
Best practices include:
Use multiple scenarios 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.
Use multiple climate models within each scenario to account for the range of outcomes due to model uncertainty. Do not rely solely on a single model or an ensemble average.
Use relevant climate data. 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.
Clearly describe key analysis uncertainties (including with any climate observations, models, and scenarios used), and how they were addressed in the analysis and/or decision process. This ensures transparency and learning among analysts and decision makers.
","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":"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.
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.
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.
","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":"Director, Central Midwest Water Science Center
U.S. Geological Survey
400 South Clinton Street, Suite 269
Iowa City, IA 52240
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.
","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}]}} ,{"id":70260933,"text":"70260933 - 2024 - Identifying and filling critical knowledge gaps can optimize financial viability of blue carbon projects in tidal wetlands","interactions":[],"lastModifiedDate":"2024-11-15T14:33:52.68755","indexId":"70260933","displayToPublicDate":"2024-10-30T08:26:46","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5738,"text":"Frontiers in Environmental Science","active":true,"publicationSubtype":{"id":10}},"title":"Identifying and filling critical knowledge gaps can optimize financial viability of blue carbon projects in tidal wetlands","docAbstract":"One of the world’s largest “blue carbon” ecosystems, Louisiana’s tidal wetlands on the US Gulf of Mexico coast, is rapidly being lost. Louisiana’s strong legal, regulatory, and monitoring framework, developed for one of the world’s largest tidal wetland systems, provides an opportunity for a programmatic approach to blue carbon accreditation to support restoration of these ecologically and economically important tidal wetlands. Louisiana’s coastal wetlands span ∼1.4 million ha and accumulate 5.5–7.3 Tg yr−1 of blue carbon (organic carbon), ∼6%–8% of tidal marsh blue carbon accumulation globally. Louisiana has a favorable governance framework to advance blue carbon accreditation, due to centralized restoration planning, long term coastal monitoring, and strong legal and regulatory frameworks around carbon. Additional restoration efforts, planned through Louisiana’s Coastal Master Plan, over 50 years are projected to create, or avoid loss of, up to 81,000 ha of wetland. Current restoration funding, primarily from Deepwater Horizon oil spill settlements, will be fully committed by the early 2030s and additional funding sources are required. Existing accreditation methodologies have not been successfully applied to coastal Louisiana’s ecosystem restoration approaches or herbaceous tidal wetland types. Achieving financial viability for accreditation of these restoration and wetland types will require expanded application of existing blue carbon crediting methodologies. It will also require expanded approaches for predicting the future landscape without restoration, such as numerical modeling, to be validated. Additional methodologies (and/or standards) would have many common elements with those currently available but may be beneficial, depending on the goals and needs of both the state of Louisiana and potential purchasers of Louisiana tidal wetland carbon credits. This study identified twenty targeted needs that will address data and knowledge gaps to maximize financial viability of blue carbon accreditation for Louisiana’s tidal wetlands. Knowledge needs were identified in five categories: legislative and policy, accreditation methodologies and standards, soil carbon flux, methane flux, and lateral carbon flux. Due to the large spatial scale and diversity of tidal wetlands, it is expected that progress in coastal Louisiana has high potential to be generalized to similar wetland ecosystems across the northern Gulf of Mexico and globally.
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Patrick","contributorId":288317,"corporation":false,"usgs":false,"family":"Megonigal","given":"J.","email":"","middleInitial":"Patrick","affiliations":[{"id":13510,"text":"Smithsonian Environmental Research Center","active":true,"usgs":false}],"preferred":false,"id":918601,"contributorType":{"id":1,"text":"Authors"},"rank":35},{"text":"Roberts, Brian J.","contributorId":341597,"corporation":false,"usgs":false,"family":"Roberts","given":"Brian","email":"","middleInitial":"J.","affiliations":[{"id":12699,"text":"Louisiana Universities Marine Consortium","active":true,"usgs":false}],"preferred":false,"id":918602,"contributorType":{"id":1,"text":"Authors"},"rank":36},{"text":"Settelmyer, Scott","contributorId":346292,"corporation":false,"usgs":false,"family":"Settelmyer","given":"Scott","email":"","affiliations":[{"id":82820,"text":"TerraCarbon LLC, Peoria, Illinoi, USA","active":true,"usgs":false}],"preferred":false,"id":918603,"contributorType":{"id":1,"text":"Authors"},"rank":37},{"text":"Staver, Lorie W.","contributorId":346293,"corporation":false,"usgs":false,"family":"Staver","given":"Lorie","email":"","middleInitial":"W.","affiliations":[{"id":82821,"text":"University of Maryland Center for Environmental Science, Horn Point Laboratory, Cambridge, Maryland, USA","active":true,"usgs":false}],"preferred":false,"id":918604,"contributorType":{"id":1,"text":"Authors"},"rank":38},{"text":"Stevens, Hilary J.","contributorId":346294,"corporation":false,"usgs":false,"family":"Stevens","given":"Hilary","email":"","middleInitial":"J.","affiliations":[{"id":82822,"text":"Restore America’s Estuaries, Washington, D.C., USA","active":true,"usgs":false}],"preferred":false,"id":918605,"contributorType":{"id":1,"text":"Authors"},"rank":39},{"text":"Sutton-Grier, Ariana Eileen 0000-0002-1242-7728","orcid":"https://orcid.org/0000-0002-1242-7728","contributorId":346295,"corporation":false,"usgs":true,"family":"Sutton-Grier","given":"Ariana","email":"","middleInitial":"Eileen","affiliations":[{"id":24693,"text":"Climate Research and Development","active":true,"usgs":true}],"preferred":true,"id":918606,"contributorType":{"id":1,"text":"Authors"},"rank":40},{"text":"Villa, Jorge A.","contributorId":343780,"corporation":false,"usgs":false,"family":"Villa","given":"Jorge","email":"","middleInitial":"A.","affiliations":[{"id":7155,"text":"University of Louisiana at Lafayette","active":true,"usgs":false}],"preferred":false,"id":918607,"contributorType":{"id":1,"text":"Authors"},"rank":41},{"text":"White, John R.","contributorId":304473,"corporation":false,"usgs":false,"family":"White","given":"John","email":"","middleInitial":"R.","affiliations":[{"id":66084,"text":"Dept. of Oceanography and Coastal Sciences, Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":918608,"contributorType":{"id":1,"text":"Authors"},"rank":42},{"text":"Waycott, Michelle","contributorId":346296,"corporation":false,"usgs":false,"family":"Waycott","given":"Michelle","email":"","affiliations":[{"id":82823,"text":"School of Biological Sciences, University of Adelaide, Adelaide, SA, Australia","active":true,"usgs":false}],"preferred":false,"id":918609,"contributorType":{"id":1,"text":"Authors"},"rank":43}]}} ,{"id":70260403,"text":"70260403 - 2024 - Predictive modeling reveals elevated conductivity relative to background levels in freshwater tributaries within the Chesapeake Bay watershed, USA","interactions":[],"lastModifiedDate":"2024-11-27T15:58:32.944541","indexId":"70260403","displayToPublicDate":"2024-10-30T07:03:12","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":19118,"text":"ES&T Water","active":true,"publicationSubtype":{"id":10}},"title":"Predictive modeling reveals elevated conductivity relative to background levels in freshwater tributaries within the Chesapeake Bay watershed, USA","docAbstract":"Elevated conductivity (i.e., specific conductance or SC) causes osmotic stress in freshwater aquatic organisms and may increase the toxicity of some contaminants. Indices of benthic macroinvertebrate integrity have declined in urban areas across the Chesapeake Bay watershed (CBW), and more information is needed about whether these declines may be due to elevated conductivity. A predictive SC model for the CBW was developed using monitoring data from the National Water Quality Portal. Predictor variables representing SC sources were compiled for nontidal reaches across the CBW. Random forests modeling was conducted to predict SC at four time periods (1999–2001, 2004–2006, 2009–2011, and 2014–2016), which were then compared to a national data set of background SC to quantify departures from background SC. Carbonate geology, impervious cover, forest cover, and snow depth were the most important variables for predicting SC. Observations and modeled results showed snow depth amplified the effect of impervious cover on SC. Elevated SC was predicted in two-thirds of reaches in the CBW, and these elevated conditions persisted over time in many areas. These results can be used in stressor identification assessments to prioritize future monitoring and to determine where management activities could be implemented to reduce salinization.
The lack of consolidated information regarding the response of wild bird species to infection with avian influenza virus (AIV) is a challenge to both conservation managers and researchers alike, with related sectors also impacted, such as public health and commercial poultry. Using two independent searches, we reviewed published literature for studies describing wild bird species experimentally infected with avian influenza to assess host species’ relative susceptibility to AIVs. Additionally, we summarize broad-scale parameters for elements such as shedding duration and minimum infectious dose that can be used in transmission modelling efforts. Our synthesis shows that waterfowl (i.e. Anatidae) compose the vast majority of published AIV pathobiology studies, whereas gulls and passerines are less represented in research despite evidence that they also are susceptible and contribute to highly pathogenic avian influenza disease dynamics. This study represents the first comprehensive effort to compile available literature regarding the pathobiology of AIVs in all wild birds in over a decade. This database can now serve as a tool to all researchers, providing generalized estimates of pathobiology parameters for a variety of wild avian families and an opportunity to critically examine and assess what is known and identify where further insight is needed.
The U.S. Geological Survey is working with Federal land management agencies to develop a series of science syntheses to support environmental effects analyses that agencies conduct to comply with the National Environmental Policy Act (NEPA). This report synthesizes science information about the potential effects of noise from oil and gas development on North American raptors, songbirds, and other small avian species. We conducted a structured search of published scientific literature to find information about noise levels produced during oil and gas development, methods for analyzing sound propagation, the effects of noise on avian species, and measures to reduce noise emissions. We follow the organization first established in U.S. Geological Survey Scientific Investigations Report 2023-5114, in which the report sections align with standard elements of NEPA analyses. We found that oil and gas development is a common source of human-caused noise on public lands and includes noise sources such as heavy construction and drilling machinery, long-term production machinery, truck traffic, and aircraft. Common techniques for predicting potential noise include field data collection using a sound level meter, inference from previously published data, and sound propagation modeling. The effects of human-caused noise on songbirds are well researched, whereas, among raptors, only owl species have been well-studied in relation to noise. Several studies have established that noise can reduce owl hunting success because many owl species are heavily reliant on hearing prey when hunting. The effects of noise on songbirds depend on several factors. Typically, birds that rely on vocal communication for mating, predator detection, and spatial orientation, and that are less able to adjust the frequencies of their vocalizations, are more vulnerable to behavioral changes and decreased fitness in noisy areas. Techniques suggested in the literature for reducing noise emissions include artificial sound barriers, seasonal and daily timing restrictions, traffic control measures, and siting infrastructure to take advantage of natural sound barriers. Public land managers can use this report by incorporating it by reference in NEPA documentation, as supplemental information, or as a general reference to find literature or identify gaps in the literature about the effects of noise from oil and gas development on raptors and songbirds.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20245087","programNote":"Prepared in cooperation with the Bureau of Land Management and the U.S. Fish and Wildlife Service","usgsCitation":"Maxwell, L.M., Rutherford, T.K., Kleist, N.J., Teige, E.C., Lehrter, R.J., Gilbert, M.A., Wood, D.J.A., Johnston, A.N., Tull, J.C., Haby, T.S., and Carter, S.K., 2024, Effects of noise from oil and gas development on raptors and songbirds—A science synthesis to inform National Environmental Policy Act analyses: U.S. Geological Survey Scientific Investigations Report 2024–5087, 66 p., https://doi.org/10.3133/sir20245087.","productDescription":"xi, 99 p.","onlineOnly":"Y","ipdsId":"IP-154746","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":463505,"rank":8,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20245087/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2024-5087"},{"id":463364,"rank":7,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2024/5087/sir20245087.xml"},{"id":463363,"rank":6,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2024/5087/images"},{"id":463212,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20235132","text":"Effects of Culverts on Habitat Connectivity in Streams—A Science Synthesis to Inform National Environmental Policy Act Analyses"},{"id":463211,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20235114","text":"Effects of Noise from Oil and Gas Development on Ungulates and Small Mammals—A Science Synthesis to Inform National Environmental Policy Act Analyses"},{"id":463210,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/fs20243028","text":"Structured Science Syntheses to Inform Decision Making on Federal Public Lands"},{"id":463209,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2024/5087/sir20245087.pdf","text":"Report","size":"3.12 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2024-5087"},{"id":463208,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2024/5087/coverthb.jpg"},{"id":497884,"rank":9,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_117742.htm","linkFileType":{"id":5,"text":"html"}}],"contact":"Director, Fort Collins Science Center
U.S. Geological Survey
2150 Centre Ave., Bldg. C
Fort Collins, CO 80526-8118
Explosive volcanic eruptions inject hot mixtures of solid particles (tephra) and gasses into the atmosphere. Entraining ambient air, these mixtures can form plumes rising tens of kilometers until they spread laterally, forming umbrella clouds. While the largest clasts tend to settle in proximity to the volcano, the smallest fragments, commonly referred to as ash (≤2 mm in diameter), can be transported over long distances, forming volcanic clouds. Tephra plumes and clouds pose significant hazards to human society, affecting infrastructure, and human health through deposition on the ground or airborne suspension at low altitudes. Additionally, volcanic clouds are a threat to aviation, during both high-risk actions such as take-off and landing and at standard cruising altitudes. The ability to monitor and forecast tephra plumes and clouds is fundamental to mitigate the hazard associated with explosive eruptions. To that end, various monitoring techniques, ranging from ground-based instruments to sensors on-board satellites, and forecasting strategies, based on running numerical models to track the position of volcanic clouds, are efficiently employed. However, some limitations still exist, mainly due to the high unpredictability and variability of explosive eruptions, as well as the multiphase and complex nature of volcanic plumes. In the next decades, advances in monitoring and computational capabilities are expected to address these limitations and significantly improve the mitigation of the risk associated with tephra plumes and clouds.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2023RG000808","usgsCitation":"Pardini, F., Barsotti, S., Bonadonna, C., de’ Michieli Vitturi, M., Folch, A., Mastin, L.G., Osores, S., and Prata, A.T., 2024, Dynamics, monitoring and forecasting of tephra in the atmosphere: Reviews of Geophysics, v. 62, e2023RG000808, 68 p., https://doi.org/10.1029/2023RG000808.","productDescription":"e2023RG000808, 68 p.","ipdsId":"IP-160162","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":466804,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2023rg000808","text":"Publisher Index Page"},{"id":463533,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"62","noUsgsAuthors":false,"publicationDate":"2024-10-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Pardini, Federica","contributorId":345831,"corporation":false,"usgs":false,"family":"Pardini","given":"Federica","email":"","affiliations":[{"id":82720,"text":"Istituto Nazionale di Geofisica e Vulcanologia (INGV), Sezione di Pisa, Pisa, Italy","active":true,"usgs":false}],"preferred":false,"id":917656,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barsotti, Sara","contributorId":199711,"corporation":false,"usgs":false,"family":"Barsotti","given":"Sara","email":"","affiliations":[],"preferred":false,"id":917657,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bonadonna, Contanza 0000-0002-2368-2193","orcid":"https://orcid.org/0000-0002-2368-2193","contributorId":339895,"corporation":false,"usgs":false,"family":"Bonadonna","given":"Contanza","email":"","affiliations":[{"id":62805,"text":"Université de Genève","active":true,"usgs":false}],"preferred":false,"id":917658,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"de’ Michieli Vitturi, Mattia","contributorId":199708,"corporation":false,"usgs":false,"family":"de’ Michieli Vitturi","given":"Mattia","email":"","affiliations":[],"preferred":false,"id":917659,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Folch, Arnau","contributorId":199712,"corporation":false,"usgs":false,"family":"Folch","given":"Arnau","email":"","affiliations":[],"preferred":false,"id":917660,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Mastin, Larry G. 0000-0002-4795-1992","orcid":"https://orcid.org/0000-0002-4795-1992","contributorId":265985,"corporation":false,"usgs":true,"family":"Mastin","given":"Larry","email":"","middleInitial":"G.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":917661,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Osores, Soledad 0009-0002-3352-9245","orcid":"https://orcid.org/0009-0002-3352-9245","contributorId":345832,"corporation":false,"usgs":false,"family":"Osores","given":"Soledad","email":"","affiliations":[{"id":82723,"text":"Servicio Meteorológico Nacional, Buenos Aires, Argentina","active":true,"usgs":false}],"preferred":false,"id":917662,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Prata, Andrew T. 0000-0001-9115-1143","orcid":"https://orcid.org/0000-0001-9115-1143","contributorId":345833,"corporation":false,"usgs":false,"family":"Prata","given":"Andrew","email":"","middleInitial":"T.","affiliations":[{"id":40928,"text":"Oxford University","active":true,"usgs":false}],"preferred":false,"id":917663,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70264867,"text":"70264867 - 2024 - Evaluating the impact of uncertainty in ground motion forecasts for post-earthquake impact modeling applications","interactions":[],"lastModifiedDate":"2025-03-26T15:38:39.371491","indexId":"70264867","displayToPublicDate":"2024-10-29T08:30:48","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7565,"text":"Earthquake Spectra Journal","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating the impact of uncertainty in ground motion forecasts for post-earthquake impact modeling applications","docAbstract":"The US Geological Survey’s (USGS) ShakeMap system provides a rapid characterization of strong ground shaking in areas directly affected by an earthquake. This study focuses on studying the aggregate effects of macroseismic shaking estimates from ShakeMap, expressed in terms of modified Mercalli intensity (MMI), when accounting for the uncertainty in forecasted ground motions. We use a Monte Carlo approach to generate numerous spatially correlated realizations of ground motions by utilizing a combination of circulant embedding and kriging techniques for efficiently handling the correlations. We then assessed the aggregate effects of shaking by looking at bin counts across these realizations. We demonstrate that the aggregate shaking regarding the mean macroseismic intensity estimates (from the ShakeMap output) is a biased representation of the aggregate shaking when shaking uncertainty is included. Incorporating shaking uncertainty can help to improve various downstream earthquake impact applications, such as the USGS Prompt Assessment of Global Earthquakes for Response (PAGER) overall earthquake fatality distribution or estimates of shaking-induced ground failure impacts from consequential earthquakes.
","language":"English","publisher":"Sage Publishing","doi":"10.1177/87552930241283201","usgsCitation":"Engler, D.T., Jaiswal, K.S., and Ganesh, M., 2024, Evaluating the impact of uncertainty in ground motion forecasts for post-earthquake impact modeling applications: Earthquake Spectra Journal, v. 41, no. 1, p. 524-546, https://doi.org/10.1177/87552930241283201.","productDescription":"23 p.","startPage":"524","endPage":"546","ipdsId":"IP-160589","costCenters":[{"id":78686,"text":"Geologic Hazards Science Center - Seismology / Geomagnetism","active":true,"usgs":true}],"links":[{"id":483880,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"41","issue":"1","noUsgsAuthors":false,"publicationDate":"2024-10-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Engler, Davis T. 0000-0002-7133-3545","orcid":"https://orcid.org/0000-0002-7133-3545","contributorId":265962,"corporation":false,"usgs":true,"family":"Engler","given":"Davis","email":"","middleInitial":"T.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":932100,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jaiswal, Kishor S. 0000-0002-5803-8007 kjaiswal@usgs.gov","orcid":"https://orcid.org/0000-0002-5803-8007","contributorId":149796,"corporation":false,"usgs":true,"family":"Jaiswal","given":"Kishor","email":"kjaiswal@usgs.gov","middleInitial":"S.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":932101,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ganesh, Mahadevan 0000-0002-7792-4119","orcid":"https://orcid.org/0000-0002-7792-4119","contributorId":352717,"corporation":false,"usgs":false,"family":"Ganesh","given":"Mahadevan","affiliations":[{"id":84292,"text":"Professor, Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":932102,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70260112,"text":"70260112 - 2024 - The projected exposure and response of a natural barrier island system to climate-driven coastal hazards","interactions":[],"lastModifiedDate":"2024-10-30T21:25:08.166742","indexId":"70260112","displayToPublicDate":"2024-10-28T10:09:48","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}},"title":"The projected exposure and response of a natural barrier island system to climate-driven coastal hazards","docAbstract":"Accelerating sea level rise (SLR) and changing storm patterns will increasingly expose barrier islands to coastal hazards, including flooding, erosion, and rising groundwater tables. We assess the exposure of Cape Lookout National Seashore, a barrier island system in North Carolina (USA), to projected SLR and storm hazards over the twenty-first century. We estimate that with 0.5 m of SLR, 47% of current subaerial barrier island area would be flooded daily, and the 1-year return period storm would flood 74%. For 20-year return period storms, over 85% is projected to be flooded for any SLR. The modelled groundwater table is already shallow (< 2 m deep), and while projected to shoal to the land surface with SLR, marine flooding is projected to overtake areas with emergent groundwater. Projected shoreline retreat reaches an average of 178 m with 1 m of SLR and no interventions, which is over 60% of the current island width at narrower locations. Compounding these hazards is subsidence, with one-third of the study area currently lowering at > 2 mm/yr. Our results demonstrate the difficulty of managing natural barrier systems such as those managed by federal park systems tasked with maintaining natural ecosystems and protecting cultural resources.
","language":"English","publisher":"Nature","doi":"10.1038/s41598-024-76749-4","usgsCitation":"Thomas, J.A., Barnard, P.L., Vitousek, S., Erikson, L.H., Parker, K.A., Nederhoff, K., Befus, K.M., and Shirzaei, M., 2024, The projected exposure and response of a natural barrier island system to climate-driven coastal hazards: Scientific Reports, v. 14, 25814, 16 p., https://doi.org/10.1038/s41598-024-76749-4.","productDescription":"25814, 16 p.","ipdsId":"IP-159766","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":466806,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-024-76749-4","text":"Publisher Index Page"},{"id":463350,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Carolina","otherGeospatial":"Cape Lookout National Seashore","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -76.00044575785073,\n 35.04289907218657\n ],\n [\n -76.06277684124831,\n 35.10241453299423\n ],\n [\n -76.46792888333269,\n 34.74467160307489\n ],\n [\n -76.53025996672974,\n 34.6678097189927\n ],\n [\n -76.6705049043746,\n 34.7105195823093\n ],\n [\n -76.69128193217362,\n 34.637899706102985\n ],\n [\n -76.4939001680816,\n 34.55666100513659\n ],\n [\n -76.00044575785073,\n 35.04289907218657\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"14","noUsgsAuthors":false,"publicationDate":"2024-10-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Thomas, Jennifer Anne 0000-0002-8338-0146","orcid":"https://orcid.org/0000-0002-8338-0146","contributorId":297988,"corporation":false,"usgs":true,"family":"Thomas","given":"Jennifer","email":"","middleInitial":"Anne","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":917041,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barnard, Patrick L. 0000-0003-1414-6476 pbarnard@usgs.gov","orcid":"https://orcid.org/0000-0003-1414-6476","contributorId":140982,"corporation":false,"usgs":true,"family":"Barnard","given":"Patrick","email":"pbarnard@usgs.gov","middleInitial":"L.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":917042,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Vitousek, Sean 0000-0002-3369-4673 svitousek@usgs.gov","orcid":"https://orcid.org/0000-0002-3369-4673","contributorId":149065,"corporation":false,"usgs":true,"family":"Vitousek","given":"Sean","email":"svitousek@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":917047,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Erikson, Li H. 0000-0002-8607-7695 lerikson@usgs.gov","orcid":"https://orcid.org/0000-0002-8607-7695","contributorId":149963,"corporation":false,"usgs":true,"family":"Erikson","given":"Li","email":"lerikson@usgs.gov","middleInitial":"H.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":917043,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Parker, Kai Alexander 0000-0002-0268-3891","orcid":"https://orcid.org/0000-0002-0268-3891","contributorId":292869,"corporation":false,"usgs":true,"family":"Parker","given":"Kai","email":"","middleInitial":"Alexander","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":917044,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Nederhoff, Kees 0000-0003-0552-3428","orcid":"https://orcid.org/0000-0003-0552-3428","contributorId":334091,"corporation":false,"usgs":false,"family":"Nederhoff","given":"Kees","affiliations":[{"id":39963,"text":"Deltares-USA","active":true,"usgs":false}],"preferred":true,"id":917045,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Befus, Kevin M.","contributorId":242636,"corporation":false,"usgs":false,"family":"Befus","given":"Kevin","email":"","middleInitial":"M.","affiliations":[{"id":36628,"text":"University of Wyoming","active":true,"usgs":false}],"preferred":false,"id":917046,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Shirzaei, Manoochehr 0000-0003-0086-3722","orcid":"https://orcid.org/0000-0003-0086-3722","contributorId":245637,"corporation":false,"usgs":false,"family":"Shirzaei","given":"Manoochehr","email":"","affiliations":[{"id":49242,"text":"Dept. of Geosciences, Virginia Tech Univ.","active":true,"usgs":false}],"preferred":false,"id":917048,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70263169,"text":"70263169 - 2024 - Multi-decadal trophic shifts in Lake Erie yellow perch Perca flavescens","interactions":[],"lastModifiedDate":"2025-01-30T16:14:56.157932","indexId":"70263169","displayToPublicDate":"2024-10-28T10:08:06","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1169,"text":"Canadian Journal of Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Multi-decadal trophic shifts in Lake Erie yellow perch Perca flavescens","title":"Multi-decadal trophic shifts in Lake Erie yellow perch Perca flavescens","docAbstract":"In Lake Erie, yellow perch Perca flavescens support vast commercial and recreational fisheries, yet populations have recently declined. Using N = 5889 yellow perch stomachs collected from 1997 to 2021, we explored trends in the feeding ecology and trophic level of yellow perch with generalized additive models. Models revealed a significant decrease in yellow perch trophic level (−0.15 trophic levels in the last decade), and significant dietary shifts. Yellow perch have shifted away from feeding on piscine prey and round goby Neogobius melanostomus over the 25-year period, and now feed on invertebrates more frequently—including invasive waterfleas (Bythotrephes longimanus and Cercopagis pengoi) and chironomids. Dietary patterns appear to reflect broad ecological changes—invasive waterfleas have proliferated while populations of forage fish and round goby have declined. Furthermore, hypoxia events have increased in duration and severity, which may explain observed increases in chironomid consumption, which are hypoxia tolerant. This study demonstrates trophic adaptability in yellow perch, which have changed feeding behavior and trophic position in response to novel invaders and changing environmental conditions.
","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjfas-2023-0348","usgsCitation":"Schmitt, J., Gorman, A., Knight, C., Dufour, M.R., Roberts, J., and Hartman, T., 2024, Multi-decadal trophic shifts in Lake Erie yellow perch Perca flavescens: Canadian Journal of Fisheries and Aquatic Sciences, v. 81, no. 11, p. 1560-1580, https://doi.org/10.1139/cjfas-2023-0348.","productDescription":"21 p.","startPage":"1560","endPage":"1580","ipdsId":"IP-140880","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":489855,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1139/cjfas-2023-0348","text":"Publisher Index Page"},{"id":481508,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Lake Erie","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -80.56325919457086,\n 41.96883002032561\n ],\n [\n -80.71352325852209,\n 42.13778067147925\n ],\n [\n -81.1801985471471,\n 42.12256709658425\n ],\n [\n -82.40972750390958,\n 41.63184115572025\n ],\n [\n -82.53711113456517,\n 41.3996082733955\n ],\n [\n -82.45403485370326,\n 41.382988331945285\n ],\n [\n -82.0829607991845,\n 41.49923867953902\n ],\n [\n -81.86223827452686,\n 41.48020592339866\n ],\n [\n -81.73401076664092,\n 41.482825773508495\n ],\n [\n -81.3851200399411,\n 41.68976914941442\n ],\n [\n -80.56325919457086,\n 41.96883002032561\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"81","issue":"11","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Schmitt, Joseph 0000-0002-8354-4067","orcid":"https://orcid.org/0000-0002-8354-4067","contributorId":221020,"corporation":false,"usgs":true,"family":"Schmitt","given":"Joseph","email":"","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":925739,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gorman, Ann Marie","contributorId":350334,"corporation":false,"usgs":false,"family":"Gorman","given":"Ann Marie","affiliations":[],"preferred":false,"id":925740,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Knight, Carey","contributorId":214230,"corporation":false,"usgs":false,"family":"Knight","given":"Carey","affiliations":[{"id":16232,"text":"Ohio Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":925741,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dufour, Mark Richard 0000-0001-6930-7666","orcid":"https://orcid.org/0000-0001-6930-7666","contributorId":291450,"corporation":false,"usgs":true,"family":"Dufour","given":"Mark","email":"","middleInitial":"Richard","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":925742,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Roberts, James J. 0000-0002-4193-610X jroberts@usgs.gov","orcid":"https://orcid.org/0000-0002-4193-610X","contributorId":5453,"corporation":false,"usgs":true,"family":"Roberts","given":"James","email":"jroberts@usgs.gov","middleInitial":"J.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":925743,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hartman, Travis","contributorId":220316,"corporation":false,"usgs":false,"family":"Hartman","given":"Travis","email":"","affiliations":[{"id":37332,"text":"Ohio Department of Natural Resources, Division of Wildlife","active":true,"usgs":false}],"preferred":false,"id":925744,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70266311,"text":"70266311 - 2024 - Predator-specific mortality of sage-grouse nests based on predator DNA on eggshells","interactions":[],"lastModifiedDate":"2025-05-05T14:44:40.283853","indexId":"70266311","displayToPublicDate":"2024-10-28T09:41:24","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Predator-specific mortality of sage-grouse nests based on predator DNA on eggshells","docAbstract":"Greater sage-grouse (hereafter sage-grouse; Centrocercus urophasianus) populations have declined across their range. Increased nest predation as a result of anthropogenic land use is one mechanism proposed to explain these declines. However, sage-grouse contend with a diverse suite of nest predators that vary in functional traits (e.g., search tactics or hunting mode) and abundance. Consequently, generalizing about factors influencing nest fate is challenging. Identifying the explicit predator species responsible for nest predation events is, therefore, critical to understanding causal mechanisms linking land use to patterns of sage-grouse nest success. Cattle grazing is often assumed to adversely affect sage-grouse recruitment by reducing grass height (and hence cover), thereby facilitating nest detection by predators. However, recent evidence found little support for the hypothesized effect of grazing on nest fate at the pasture scale. Rather, nest success appears to be similar on pastures grazed at varying intensities. One possible explanation for the lack of observed effect involves a localized response by one or more nest predators. The presence of cattle may cause a temporary reduction in predator density and/or use within a pasture (the cattle avoidance hypothesis). The cattle avoidance hypothesis predicts a decreased probability of at least one sage-grouse nest predator predating sage-grouse nests in pastures with livestock relative to pastures without livestock present during the nesting season. To test the cattle avoidance hypothesis, we collected predator DNA from eggshells from predated nests and used genetic methods to identify the sage-grouse nest predator(s) responsible for the predation event. We evaluated the influence of habitat and grazing on predator-specific nest predation. We evaluated the efficacy of our genetic method by deploying artificial nests with trail cameras and compared the results of our genetic method to the species captured via trail camera. Our molecular methods identified at least one nest predator captured predating artificial nests via trail camera for 33 of 35 (94%) artificial nests. We detected nest predators via our molecular analysis at 76 of 114 (67%) predated sage-grouse nests. The primary predators detected at sage-grouse nests were coyotes (Canis latrans) and corvids (Corvidea). Grazing did not influence the probability of nest predation by either coyotes or corvids. Sagebrush canopy cover was negatively associated with the probability a coyote predated a nest, distance to water was positively associated with the probability a corvid predated a nest, and average minimum temperature was negatively associated with the probability that either a coyote or a corvid predated a nest. Our study provides a framework for implementing an effective, non-invasive method for identifying sage-grouse nest predators that can be used to better understand how management actions at local and regional scales may impact an important component of sage-grouse recruitment.
","language":"English","publisher":"Wiley","doi":"10.1002/ece3.70213","usgsCitation":"Helmstetter, N.A., Conway, C.J., Roberts, S., Adams, J., Makela, P., and Waits, L., 2024, Predator-specific mortality of sage-grouse nests based on predator DNA on eggshells: Ecology and Evolution, v. 14, no. 10, e70213, 19 p., https://doi.org/10.1002/ece3.70213.","productDescription":"e70213, 19 p.","ipdsId":"IP-166147","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":487947,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.70213","text":"Publisher Index Page"},{"id":485377,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -112.84878592693147,\n 44.720752546676636\n ],\n [\n -116.22953206733101,\n 44.720752546676636\n ],\n [\n -116.22953206733101,\n 41.995370325478774\n ],\n [\n -112.84878592693147,\n 41.995370325478774\n ],\n [\n -112.84878592693147,\n 44.720752546676636\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"14","issue":"10","noUsgsAuthors":false,"publicationDate":"2024-10-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Helmstetter, Nolan A.","contributorId":287004,"corporation":false,"usgs":false,"family":"Helmstetter","given":"Nolan","email":"","middleInitial":"A.","affiliations":[{"id":39599,"text":"ui","active":true,"usgs":false}],"preferred":false,"id":935533,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Conway, Courtney J. 0000-0003-0492-2953 cconway@usgs.gov","orcid":"https://orcid.org/0000-0003-0492-2953","contributorId":2951,"corporation":false,"usgs":true,"family":"Conway","given":"Courtney","email":"cconway@usgs.gov","middleInitial":"J.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":935534,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Roberts, Shane","contributorId":279606,"corporation":false,"usgs":false,"family":"Roberts","given":"Shane","affiliations":[{"id":56023,"text":"idfg","active":true,"usgs":false}],"preferred":false,"id":935535,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Adams, Jennifer R.","contributorId":341225,"corporation":false,"usgs":false,"family":"Adams","given":"Jennifer R.","affiliations":[{"id":36394,"text":"University of Idaho","active":true,"usgs":false}],"preferred":false,"id":935536,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Makela, Paul D.","contributorId":354380,"corporation":false,"usgs":false,"family":"Makela","given":"Paul D.","affiliations":[{"id":37086,"text":"U.S. Bureau of Land Management","active":true,"usgs":false}],"preferred":false,"id":935537,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Waits, Lisette P.","contributorId":338452,"corporation":false,"usgs":false,"family":"Waits","given":"Lisette P.","affiliations":[{"id":36394,"text":"University of Idaho","active":true,"usgs":false}],"preferred":false,"id":935538,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ]}