The U.S. Geological Survey-managed ShakeAlert® earthquake early warning system is the first public alerting system in the United States to provide rapid mass notification when an earthquake is detected. Although public alert delivery via mobile phones began in California in 2019 followed by Oregon and Washington in 2021, little is known about what might drive widespread implementation in at-risk institutional settings such as schools. For example, there has been limited research on how to best integrate earthquake early warning into existing emergency plans, alert systems, and drills to keep school children and personnel safe in an earthquake. To address this gap, in the spring of 2022, every school district superintendent in Alaska, California, Oregon, and Washington was sent a 15-min online survey. The survey assessed superintendent knowledge of ShakeAlert, preferences for alert messaging, and perceived opportunities and barriers to incorporating the system in schools. The results showed that superintendents had low awareness of ShakeAlert but held positive perceptions of the system's potential to enable life-saving protective actions. A major barrier to adoption included the perceived financial cost of implementing and maintaining the system. There were some statistically significant differences in state responses, and future research could investigate the specific needs of each state based on school district size and composition, hazard exposure, and earthquake experience. Together these findings can help inform targeted strategies to increase ShakeAlert adoption in schools and ultimately improve the safety of school children and staff during earthquakes.
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Cisco historically supported large commercial fisheries in the Great Lakes during the late 1800s and early 1900s, but many populations declined and never recovered. Restoration efforts focusing on re-establishing cisco in the Great Lakes are underway, but increasing water temperatures may hinder these efforts. Therefore, we examined aerobic scope and thermal tolerance of allopatric cisco populations from different latitudes and habitats to determine if a southern latitude population (Crooked Lake, Indiana, USA) near the southern edge of cisco distribution was better adapted to withstand warmer water temperatures than a northern latitude population (Les Cheneaux Islands, Michigan, USA; Lake Huron). As expected, both stocks demonstrated increases in metabolic rates and absolute aerobic scope with increased temperature. Northern cisco had significantly lower aerobic scope compared to southern cisco at both treatment temperatures of 10 and 13 °C. Both cisco stocks had high thermal tolerances when challenged by temperatures increased to 20 and 23 °C but low tolerances at 26 °C. Cisco thermal tolerances increased with acclimation temperature, but we did not detect a difference in thermal tolerances between northern and southern cisco. Although southern cisco had higher capacity for aerobic metabolism, both stock sources had high thermal tolerances at the upper end of their thermal limits. Therefore, either population would be likely suitable for reintroduction into Great Lakes habitats, even with expected warming in the future.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jglr.2024.102415","usgsCitation":"Simonson, M.A., Bunnell, D., Madenjian, C.P., Keeler, K., and Schmitt, J., 2024, Comparison of cisco (Coregonus artedi) aerobic scope and thermal tolerance between two latitudinally-separated populations: Journal of Great Lakes Research, v. 50, no. 5, 102415, 15 p., https://doi.org/10.1016/j.jglr.2024.102415.","productDescription":"102415, 15 p.","ipdsId":"IP-163760","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":433551,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Indiana, Michigan","otherGeospatial":"Crooked Lake, Lake Huron, Les Cheneaux Islands","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -85.03178580679142,\n 41.67704854292987\n ],\n [\n -85.04022127240248,\n 41.681592163341264\n ],\n [\n -85.05202177523562,\n 41.68084213613412\n ],\n [\n -85.05001009167275,\n 41.67730644213748\n ],\n [\n -85.05708836112665,\n 41.67907615186607\n ],\n [\n -85.06554000528172,\n 41.67680253578493\n ],\n [\n -85.07195756200889,\n 41.68915760089371\n ],\n [\n -85.08649731967846,\n 41.6972246451536\n ],\n [\n -85.08816388966483,\n 41.69344382786758\n ],\n [\n -85.08038942342932,\n 41.68562927086904\n ],\n [\n -85.06959145739484,\n 41.67125444049145\n ],\n [\n -85.05135405535435,\n 41.66671827650961\n ],\n [\n -85.03683916319395,\n 41.66495144604414\n ],\n [\n -85.03178580679142,\n 41.67704854292987\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -84.46412303427357,\n 46.00609133034004\n ],\n [\n -84.46412303427357,\n 45.9152499898876\n ],\n [\n -84.23127103952208,\n 45.9152499898876\n ],\n [\n -84.23127103952208,\n 46.00609133034004\n ],\n [\n -84.46412303427357,\n 46.00609133034004\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"50","issue":"5","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Simonson, Martin Albert 0000-0002-1284-8055","orcid":"https://orcid.org/0000-0002-1284-8055","contributorId":343964,"corporation":false,"usgs":true,"family":"Simonson","given":"Martin","email":"","middleInitial":"Albert","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":912481,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bunnell, David 0000-0003-3521-7747","orcid":"https://orcid.org/0000-0003-3521-7747","contributorId":217344,"corporation":false,"usgs":true,"family":"Bunnell","given":"David","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":912482,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Madenjian, Charles P. 0000-0002-0326-164X cmadenjian@usgs.gov","orcid":"https://orcid.org/0000-0002-0326-164X","contributorId":2200,"corporation":false,"usgs":true,"family":"Madenjian","given":"Charles","email":"cmadenjian@usgs.gov","middleInitial":"P.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":912483,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Keeler, Kevin 0000-0002-8118-0060","orcid":"https://orcid.org/0000-0002-8118-0060","contributorId":203484,"corporation":false,"usgs":true,"family":"Keeler","given":"Kevin","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":912484,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"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":912485,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70261614,"text":"70261614 - 2024 - Aurora: An open-source Python implementation of the EMTF package for magnetotelluric data processing using MTH5 and mt-metadata","interactions":[],"lastModifiedDate":"2024-12-17T15:37:10.567627","indexId":"70261614","displayToPublicDate":"2024-08-22T09:35:56","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5929,"text":"Journal of Open Source Software","active":true,"publicationSubtype":{"id":10}},"title":"Aurora: An open-source Python implementation of the EMTF package for magnetotelluric data processing using MTH5 and mt-metadata","docAbstract":"The Aurora software package robustly estimates single station and remote reference electromagnetic transfer functions (TFs) from magnetotelluric (MT) time series. Aurora is part of an open-source processing workflow that leverages the self-describing data container MTH5, which in turn leverages the general mt-metadata framework to manage metadata. These pre-existing packages simplify the processing by providing managed data structures, allowing for transfer functions to be generated with only a few lines of code. The processing depends on two inputs -- a table defining the data to use for TF estimation, and a JSON file specifying the processing parameters, both of which are generated automatically, and can be modified if desired. Output TFs are returned as mt_metadata objects, and can be exported to a variety of common formats for plotting, modeling and inversion.
","language":"English","publisher":"Open Source Initiative","doi":"10.21105/joss.06832","usgsCitation":"Kappler, K., Peacock, J., Egbert, G.D., Frassetto, A., Heagy, L., Kelbert, A., Keyson, L., Oldenburg, D.W., Ronan, T., and Sweet, J., 2024, Aurora: An open-source Python implementation of the EMTF package for magnetotelluric data processing using MTH5 and mt-metadata: Journal of Open Source Software, v. 9, no. 100, 6832, 7 p., https://doi.org/10.21105/joss.06832.","productDescription":"6832, 7 p.","ipdsId":"IP-164541","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":466956,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"http://dx.doi.org/10.21105/joss.06832","text":"Publisher Index Page"},{"id":465194,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","issue":"100","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Kappler, Karl 0000-0002-1877-1255","orcid":"https://orcid.org/0000-0002-1877-1255","contributorId":345189,"corporation":false,"usgs":false,"family":"Kappler","given":"Karl","email":"","affiliations":[{"id":82517,"text":"IMDEX Technology USA, LLC","active":true,"usgs":false}],"preferred":false,"id":921185,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Peacock, Jared R. 0000-0002-0439-0224","orcid":"https://orcid.org/0000-0002-0439-0224","contributorId":210082,"corporation":false,"usgs":true,"family":"Peacock","given":"Jared R.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":921186,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Egbert, Gary D.","contributorId":187462,"corporation":false,"usgs":false,"family":"Egbert","given":"Gary","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":921187,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Frassetto, Andrew 0000-0002-8818-3731","orcid":"https://orcid.org/0000-0002-8818-3731","contributorId":345192,"corporation":false,"usgs":false,"family":"Frassetto","given":"Andrew","email":"","affiliations":[{"id":82518,"text":"Incorporated Research Institutes for Seismology","active":true,"usgs":false}],"preferred":false,"id":921327,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Heagy, Lindsey 0000-0002-1551-5926","orcid":"https://orcid.org/0000-0002-1551-5926","contributorId":345190,"corporation":false,"usgs":false,"family":"Heagy","given":"Lindsey","email":"","affiliations":[{"id":78772,"text":"University of British Columbia, Canada","active":true,"usgs":false}],"preferred":false,"id":921328,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kelbert, Anna 0000-0003-4395-398X akelbert@usgs.gov","orcid":"https://orcid.org/0000-0003-4395-398X","contributorId":184053,"corporation":false,"usgs":true,"family":"Kelbert","given":"Anna","email":"akelbert@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":921329,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Keyson, Laura","contributorId":347262,"corporation":false,"usgs":false,"family":"Keyson","given":"Laura","email":"","affiliations":[{"id":83114,"text":"Earthscope USA","active":true,"usgs":false}],"preferred":false,"id":921188,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Oldenburg, Douglas W. 0000-0002-4327-2124","orcid":"https://orcid.org/0000-0002-4327-2124","contributorId":304117,"corporation":false,"usgs":false,"family":"Oldenburg","given":"Douglas","email":"","middleInitial":"W.","affiliations":[{"id":65972,"text":"Geophysical Inversion Facility (GIF), Department of Earth, Ocean and Atmospheric Sciences, University of British Columbia","active":true,"usgs":false}],"preferred":false,"id":921330,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Ronan, Timothy 0000-0001-8450-9573","orcid":"https://orcid.org/0000-0001-8450-9573","contributorId":345191,"corporation":false,"usgs":false,"family":"Ronan","given":"Timothy","email":"","affiliations":[{"id":82518,"text":"Incorporated Research Institutes for Seismology","active":true,"usgs":false}],"preferred":false,"id":921189,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Sweet, Justin 0000-0001-7323-9758","orcid":"https://orcid.org/0000-0001-7323-9758","contributorId":347263,"corporation":false,"usgs":false,"family":"Sweet","given":"Justin","email":"","affiliations":[{"id":83114,"text":"Earthscope USA","active":true,"usgs":false}],"preferred":false,"id":921331,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70261213,"text":"70261213 - 2024 - A scaling relationship for the width of secondary deformation around strike-slip faults","interactions":[],"lastModifiedDate":"2024-12-02T14:46:56.231325","indexId":"70261213","displayToPublicDate":"2024-08-22T08:42:13","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3525,"text":"Tectonophysics","active":true,"publicationSubtype":{"id":10}},"title":"A scaling relationship for the width of secondary deformation around strike-slip faults","docAbstract":"Simple mechanical arguments suggest that slip along interlocked, rough faults, damages surrounding rocks. The same arguments require that the scale of secondary damage is proportional to the size of geometric irregularities along the main fault. This relationship could apply at all scales, but has, so far, been difficult to observe at the 10s to 100 s of km scales of large, natural faults, often because large-scale deformation is distributed across wide, complex plate-boundary fault systems, like the San Andreas Fault. The geometry and geology of another large-scale plate-boundary strike slip fault—the Queen Charlotte Fault (QCF)—is, in contrast, especially simple. Here, we show that observations of secondary deformation are well-aligned with predictions of stress variations caused by geometric irregularities along the QCF, suggesting a geometric relationship between primary fault geometry and secondary deformation. The analytic stress solution reveals that the highest stresses and highest likelihood of failure are confined to a zone of influence (ZOI) with a width quantified by
Decadal scale lake drying in interior Alaska results in lake margin colonization by willow shrub and graminoid vegetation, but the effects of these changes on plant production, biodiversity, soil properties, and soil microbial communities are not well known. We studied changes in soil organic carbon (SOC) and nitrogen (N) storage, plant and microbial community composition, and soil microbial activities in drying and non-drying lakes in the Yukon Flats National Wildlife Refuge. Historic changes in lake area were determined using Landsat imagery. Results showed that SOC storage in drying lake margins declined by 0.13 kg C m−2 yr−1 over 30 years of exposure of lake sediments, with no significant change in soil N. Lake drying resulted in an increase in graminoid and shrub aboveground net primary production (ANPP, +3% yr−1) with little change in plant functional composition. Increases in ANPP were similar in magnitude (but opposite in sign) to losses in SOC over a 30-year drying trend. Potential decomposition rates and soil enzyme activities were lower in drying lake margins compared to stable lake margins, possibly due to high salinities in drying lake margin soils. Microbial communities shifted in response to changing plant communities, although they still retained a legacy of the previous plant community. Understanding how changing lake hydrology impacts the ecology and biogeochemistry of lake margin terrestrial ecosystems is an underexamined phenomenon with large impacts to landscape processes.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2023JG007819","usgsCitation":"Patil, V.P., McFarland, J., Wickland, K., Manies, K.L., Winterstein, M., Hollingsworth, T., Euskirchen, E., and Waldrop, M., 2024, The effect of drying boreal lakes on plants, soils, and microbial communities in lake margin habitats: JGR Biogeosciences, v. 129, no. 8, e2023JG007819, 21 p., https://doi.org/10.1029/2023JG007819.","productDescription":"e2023JG007819, 21 p.","ipdsId":"IP-139844","costCenters":[{"id":65299,"text":"Alaska Science Center Ecosystems","active":true,"usgs":true}],"links":[{"id":439200,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2023jg007819","text":"Publisher Index Page"},{"id":433403,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Yukon Flats National Wildlife Refuge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -150.14311428675356,\n 66.58339320669828\n ],\n [\n -150.0613509618515,\n 65.52747431340518\n ],\n [\n -143.489470862569,\n 65.54657614460567\n ],\n [\n -143.48736112738945,\n 66.54807699281983\n ],\n [\n -150.14311428675356,\n 66.58339320669828\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"129","issue":"8","noUsgsAuthors":false,"publicationDate":"2024-08-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Patil, Vijay P. 0000-0002-9357-194X vpatil@usgs.gov","orcid":"https://orcid.org/0000-0002-9357-194X","contributorId":203676,"corporation":false,"usgs":true,"family":"Patil","given":"Vijay","email":"vpatil@usgs.gov","middleInitial":"P.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":false,"id":912009,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McFarland, Jack 0000-0001-9672-8597","orcid":"https://orcid.org/0000-0001-9672-8597","contributorId":214819,"corporation":false,"usgs":true,"family":"McFarland","given":"Jack","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":912012,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wickland, Kimberly 0000-0002-6400-0590","orcid":"https://orcid.org/0000-0002-6400-0590","contributorId":208471,"corporation":false,"usgs":true,"family":"Wickland","given":"Kimberly","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":912011,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Manies, Kristen L. 0000-0003-4941-9657 kmanies@usgs.gov","orcid":"https://orcid.org/0000-0003-4941-9657","contributorId":2136,"corporation":false,"usgs":true,"family":"Manies","given":"Kristen","email":"kmanies@usgs.gov","middleInitial":"L.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":912013,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Winterstein, Mark","contributorId":343792,"corporation":false,"usgs":false,"family":"Winterstein","given":"Mark","email":"","affiliations":[{"id":13117,"text":"Institute of Arctic Biology, University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":912014,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hollingsworth, Teresa N.","contributorId":343793,"corporation":false,"usgs":false,"family":"Hollingsworth","given":"Teresa N.","affiliations":[{"id":37389,"text":"U.S. Forest Service","active":true,"usgs":false}],"preferred":false,"id":912015,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Euskirchen, Eugénie S.","contributorId":83378,"corporation":false,"usgs":false,"family":"Euskirchen","given":"Eugénie S.","affiliations":[{"id":13117,"text":"Institute of Arctic Biology, University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":912016,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Waldrop, Mark 0000-0003-1829-7140","orcid":"https://orcid.org/0000-0003-1829-7140","contributorId":216758,"corporation":false,"usgs":true,"family":"Waldrop","given":"Mark","affiliations":[],"preferred":true,"id":912010,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70259304,"text":"70259304 - 2024 - Remote sensing large-wood storage downstream of reservoirs during and after dam removal: Elwha River, Washington, USA","interactions":[],"lastModifiedDate":"2024-10-03T12:15:08.069344","indexId":"70259304","displayToPublicDate":"2024-08-22T07:10:44","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5026,"text":"Earth and Space Science","active":true,"publicationSubtype":{"id":10}},"title":"Remote sensing large-wood storage downstream of reservoirs during and after dam removal: Elwha River, Washington, USA","docAbstract":"Large wood is an integral part of many rivers, often defining river-corridor morphology and habitat, but its occurrence, magnitude, and evolution in a river system are much less well understood than the sedimentary and hydraulic components, and due to methodological limitations, have seldom previously been mapped in substantial detail. We present a new method for this, representing a substantial advance in automated deep-learning-based image segmentation. From these maps, we measured large wood and sediment deposits from high-resolution orthoimages to explore the dynamics of large wood in two reaches of the Elwha River, Washington, USA, between 2012 and 2017 as it adjusted to upstream dam removals. The data set consists of a time series of orthoimages (12.5-cm resolution) constructed using Structure-from-Motion photogrammetry on imagery from 14 aerial surveys. Model training was optimized to yield maximum accuracy for estimated wood areas, compared to manually digitized wood, therefore model development and intended application were coupled. These fully reproducible methods and model resulted in a maximum of 15% error between observed and estimated total wood areas and wood deposit size-distributions over the full spatio-temporal extent of the data. Areal extent of wood in the channel margin approximately doubled in the years following dam removal, with greatest increases in large wood in wider, lower-gradient sections. Large-wood deposition increased between the start of dam removal (2011) and winter 2013, then plateaued. Sediment bars continued to grow up until 2016/17, assisted by a partially static wood framework deposited predominantly during the period up to winter 2013.
The Redeye Bass Micropterus coosae is a piscivore introduced into California, which has become a threat to the state's endemic freshwater fishes. It has eliminated native fishes from the middle reaches of the Cosumnes River, our study stream, which is the largest stream without a major dam on its main stem in the Sacramento–San Joaquin River drainage, central California, USA. We thoroughly documented its novel life history and ecology in California to shed light on why it has been such a successful invader despite its relatively small native range.
Over 4000 stable carbon and nitrogen isotope samples were utilized to refine our understanding of fish trophic position within the river food web, along with a stable isotope mixing model that accounts for uncertainty in trophic enrichment data.
Growth was slow, with an adult size range of 9–25 cm standard length (SL), although few were larger than 15-cm SL (5–6 years old). Stable isotope analyses showed that Redeye Bass dominate the river ecosystem to the exclusion of most native fishes, occupying multiple trophic levels and microhabitats. Adults largely consumed non-native crayfish and large aquatic insects, while juveniles consumed aquatic insects, the size of prey increasing with Redeye Bass length. There was no evidence of cannibalism. Redeye Bass have effectively occupied the diverse trophic positions of at least four native fish species and have altered the trophic position of Rainbow Trout Oncorhynchus mykiss in sites where they co-occur with bass.
The introduction of Redeye Bass poses a continuing threat to native stream fishes in California and elsewhere.
","language":"English","publisher":"American Fisheries Society","doi":"10.1002/tafs.10477","usgsCitation":"Long, B.C., Moyle, P.B., Young, M.J., and Crain, P.K., 2024, Age, growth, and trophic ecology of the Redeye Bass, an introduced invader of California rivers: Transactions of the American Fisheries Society, v. 153, no. 5, p. 559-575, https://doi.org/10.1002/tafs.10477.","productDescription":"17 p.","startPage":"559","endPage":"575","ipdsId":"IP-165585","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":439201,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/tafs.10477","text":"Publisher Index Page"},{"id":433151,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"153","issue":"5","noUsgsAuthors":false,"publicationDate":"2024-08-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Long, Beth C.","contributorId":343631,"corporation":false,"usgs":false,"family":"Long","given":"Beth","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":911566,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Moyle, Peter B.","contributorId":117099,"corporation":false,"usgs":false,"family":"Moyle","given":"Peter","email":"","middleInitial":"B.","affiliations":[{"id":7214,"text":"University of California, Davis","active":true,"usgs":false}],"preferred":false,"id":911567,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Young, Matthew J. 0000-0001-9306-6866 mjyoung@usgs.gov","orcid":"https://orcid.org/0000-0001-9306-6866","contributorId":206255,"corporation":false,"usgs":true,"family":"Young","given":"Matthew","email":"mjyoung@usgs.gov","middleInitial":"J.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":911568,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Crain, Patrick K.","contributorId":343634,"corporation":false,"usgs":false,"family":"Crain","given":"Patrick","email":"","middleInitial":"K.","affiliations":[{"id":13109,"text":"ICF International","active":true,"usgs":false}],"preferred":false,"id":911569,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70257725,"text":"70257725 - 2024 - Social vulnerability and water insecurity in the western US: A systematic review of framings, indicators, and uncertainty","interactions":[],"lastModifiedDate":"2024-08-26T11:36:09.165908","indexId":"70257725","displayToPublicDate":"2024-08-22T06:23:43","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Social vulnerability and water insecurity in the western US: A systematic review of framings, indicators, and uncertainty","docAbstract":"Water insecurity poses a complex challenge for the western United States. Large populations are exposed and susceptible to physical and social factors that can leave them with precarious access to sufficient water supplies. Consideration of social issues by water managers can help ensure equitable supply. However, how social factors affect water insecurity conditions remains unclear. This paper reviews literature on how social vulnerability influences water insecurity in the western United States. Through a meta-analysis, indicators measuring how dimensions of social vulnerability influence water insecurity were classified and hierarchical clustering was used to characterize the relationships among these vulnerability dimensions for the largest water-users—the agricultural and municipal sectors. The study then assessed uncertainty associated with social vulnerability dimensions and their indicators. There is greatest evidence for the influence of demographic characteristics, socioeconomic status, and exposure. Indicators of these determinants were mainly significant and exacerbated conditions of water insecurity. Evidence for indicators of social dependence and special needs populations was limited, although studies assessing these factors showed significant agreement on their influence on water insecurity. Conceptual framings of social vulnerability and water security determined which indicators were measured, whereas studies of the water-use sectors focused on differing associations of social vulnerability. These findings indicate the importance of recognizing the different contexts posed by water-use sectors and diverse conceptual framings. Further, some determinants such as living conditions remain important but underexplored drivers of a community's experience of water insecurity. Understanding the uncertainty associated with these measures has implications to equitable decision making.
No abstract available.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Bulletin of the American Meteorological Society, State of the Climate, 2023 report","largerWorkSubtype":{"id":9,"text":"Other Report"},"language":"English","publisher":"American Meteorological Society","doi":"10.1175/BAMS-D-24-0101.1","usgsCitation":"Burgess, D., Wolken, G., Wouters, B., Andreassen, L., Florentine, C., Kohler, J., Luks, B., Palsson, F., Sass, L., Thomson, L., and Thorsteinsson, T., 2024, Glaciers and ice caps outside Greenland, v. 105, no. 8, 4 p., https://doi.org/10.1175/BAMS-D-24-0101.1.","productDescription":"4 p.","startPage":"S307","endPage":"S310","ipdsId":"IP-162903","costCenters":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":466959,"rank":0,"type":{"id":41,"text":"Open Access External Repository 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B.","contributorId":298653,"corporation":false,"usgs":false,"family":"Luks","given":"B.","email":"","affiliations":[],"preferred":false,"id":916442,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Palsson, F.","contributorId":345407,"corporation":false,"usgs":false,"family":"Palsson","given":"F.","email":"","affiliations":[{"id":82570,"text":"Institute of Earth Sciences, University of Iceland, Reykjavík, Iceland","active":true,"usgs":false}],"preferred":false,"id":916439,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Sass, Louis C. 0000-0003-4677-029X lsass@usgs.gov","orcid":"https://orcid.org/0000-0003-4677-029X","contributorId":3555,"corporation":false,"usgs":true,"family":"Sass","given":"Louis C.","email":"lsass@usgs.gov","affiliations":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true},{"id":114,"text":"Alaska Science 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Washington"},"lastModifiedDate":"2026-02-03T18:14:38.644212","indexId":"sir20245026v2","displayToPublicDate":"2024-08-21T14:09:17","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":"2024-5026","chapter":"D-E","displayTitle":"Numerical Model of the Groundwater-Flow System Near the Southeastern Part of Puget Sound, Washington","title":"Numerical model of the groundwater-flow system near the southeastern part of Puget Sound, Washington","docAbstract":"Groundwater flow in the active model area (AMA) was simulated using a groundwater-flow model. A steady-state model version of the model simulates equilibrium conditions, and a transient model version simulates monthly variability. The model corresponds to the physical and temporal dimensions of the conceptual model and groundwater budget. The steady-state model version represents average conditions for an 11-year period (January 1, 2005–December 31, 2015), and the transient model represents monthly hydrologic variability within that period. The 13-layer model was constructed using MODFLOW-NWT with a uniformly spaced grid consisting of 416 rows, 433 columns, and cells with a horizontal dimension of 500 feet (ft) on a side.
The model was calibrated to measured values of water levels in wells and lakes and estimated base flow for selected streamflow measurement stations, commonly referred to as streamgages. Model calibration was accomplished using a combination of manual and automatic methods, including the Model-Independent Parameter Estimation (PEST) program that adjusted model input parameters with the aim of minimizing the difference between estimated and model-simulated values of hydraulic head and base flow.
Model boundary conditions consist of all simulated groundwater inflow to and outflow from the AMA. For example, a stream reach that simulates a gain from or loss to groundwater is a boundary condition that allows water to exit or enter, respectively, the groundwater system. Other boundary conditions include springs, seeps, precipitation recharge, groundwater exchange with lakes and Puget Sound, and groundwater pumping. A comparison of the estimated groundwater budget to that simulated by the steady-state model version indicates that the relative percentages of total inflow or total outflow for six major categories of boundary conditions are similar for the two budgets.
The model was used to simulate three suites of scenarios of potential drought and water-use changes. Scenario 1 suite consisted of the steady-state model version that was run with 0, 15, 20, and 25 percent reduction of precipitation recharge to assess the corresponding reductions in base flow with decreasing recharge. The last simulation for the scenario 1 suite consisted of the transient model version simulating 3 years of consecutive seasonal drought, defined by the months of May through September, to assess the corresponding base-flow reductions. Scenario 2 suite consisted of the steady-state model version with all simulated groundwater use removed, compared with a simulation that includes current groundwater use to evaluate changes to potentiometric surfaces and base flows. Scenario 3 suite consisted of a transient model version of the model that simulated pumping increases for four different categories of water-supply wells (compared to no pumping increases) to evaluate resulting reductions in base flow. Although, these scenarios provide examples of model applications and useful insights, many other scenarios could be simulated. A description of how to download the model is described in the body of this report.
Uncertainty is associated with most model inputs. Groundwater levels, lake levels, and land-surface altitudes are relatively certain; other model inputs are far less certain, including precipitation recharge, base flow, hydraulic properties, water use, and the three-dimensional structure of subsurface hydrogeologic units. Models are useful not because of high levels of accuracy of all model inputs, but because they combine the best information and estimates available, thereby providing the best predictions available related to physical processes.
The model described in this report simulates groundwater flow on a regional scale, which has inherent limitations for simulating hydrologic scenarios at local scales. Model structures and inputs were generalized to be consistent with this regional scale. For example, the actual groundwater system has much greater heterogeneity of hydraulic conductivity than is possible within the model’s degrees of freedom. Variations in hydraulic gradients over distances less than 500 ft cannot be simulated. The distances between model features, such as a pumping well and a stream, must be placed at 500-ft intervals and are co-located if both features are within the same model cell.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20245026v2","collaboration":"Prepared in cooperation with the Cities of Auburn, Milton, Puyallup, Sumner, and Tacoma; Pierce Conservation District; Pierce County Public Works; Washington State Department of Health; Washington State Department of Ecology; Thurston County Public Utility District; Cascade Water Alliance; Lakehaven Utility District; Lakewood Water District; Firgrove Mutual Water Company; Fruitland Mutual Water Company; Spanaway Water Company; Summit Water & Supply Company; and Mt. View-Edgewood Water Company","usgsCitation":"Long, A.J., Wright, E.E., Fuhrig, L.T., and Bright, V.A.L., 2024, Numerical model of the groundwater-flow system near the southeastern part of Puget Sound, Washington, v. 2 of Welch, W.B., and Long, A.J., eds., Characterization of groundwater resources near the southeastern part of Puget Sound, Washington, 2 chap. 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Washington"},{"id":432079,"rank":13,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2024/5026/v2/data/sir20245026v2_Table1.11.csv","text":"Table 1.11","size":"8 KB","linkFileType":{"id":7,"text":"csv"},"description":"SIR 2024-5026 Vol 2 Table 1.11","linkHelpText":"- Supplemental hydraulic-head targets for the steady-state model version set equal to the land surface to prevent groundwater flooding and corresponding simulated values, near the southeastern part of Puget Sound, Washington"},{"id":432074,"rank":8,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2024/5026/v2/data/sir20245026v2_Table1.6.csv","text":"Table 1.6","size":"637 KB","linkFileType":{"id":7,"text":"csv"},"description":"SIR 2024-5026 Vol 2 Table 1.6","linkHelpText":"- Time-series records of measured and simulated hydraulic-head values (transient model version) for selected wells used, near the southeastern part of Puget Sound, Washington, 2005–15"},{"id":432087,"rank":21,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2024/5026/v2/sir20245026v2.XML","linkFileType":{"id":8,"text":"xml"},"description":"SIR 2024-5026 Vol 2 XML"},{"id":432066,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2024/5026/v2/sir20245026v2.jpg"},{"id":432067,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2024/5026/v2/sir20245026v2.pdf","size":"10.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2024-5026 Vol 2 PDF"},{"id":432069,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2024/5026/v2/data/sir20245026v2_Table1.1.csv","text":"Table 1.1","size":"995 KB","linkFileType":{"id":7,"text":"csv"},"description":"SIR 2024-5026 Vol 2 Table 1.1","linkHelpText":"- Streamflow-Routing (SFR) Package specifications by reach"},{"id":432070,"rank":4,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2024/5026/v2/data/sir20245026v2_Table1.2.csv","text":"Table 1.2","size":"5 KB","linkFileType":{"id":7,"text":"csv"},"description":"SIR 2024-5026 Vol 2 Table 1.2","linkHelpText":"- Estimated monthly average base flow estimated for Coal, Boise, and Scatter Creeks where they enter the active model area, near the southeastern part of Puget Sound, Washington, 2005–15"},{"id":432071,"rank":5,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2024/5026/v2/data/sir20245026v2_Table1.3.csv","text":"Table 1.3","size":"10 KB","linkFileType":{"id":7,"text":"csv"},"description":"SIR 2024-5026 Vol 2 Table 1.3","linkHelpText":"- Estimated monthly average base flow estimated for selected streams where they enter the active model area, the Buckley diversion (inflow to Lake Tapps), and outflow from Lake Tapps, near the southeastern part of Puget Sound, Washington, 2005–15"},{"id":432072,"rank":6,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2024/5026/v2/data/sir20245026v2_Table1.4.csv","text":"Table 1.4","size":"6 KB","linkFileType":{"id":7,"text":"csv"},"description":"SIR 2024-5026 Vol 2 Table 1.4","linkHelpText":"- Monthly average water levels for American, Gravelly, Steilacoom, and Spanaway Lakes, and Lake Tapps, derived from measured and estimated values, near the southeastern part of Puget Sound, Washington, 2005–15"},{"id":432073,"rank":7,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2024/5026/v2/data/sir20245026v2_Table1.5.csv","text":"Table 1.5","size":"6.7 MB","linkFileType":{"id":7,"text":"csv"},"description":"SIR 2024-5026 Vol 2 Table 1.5","linkHelpText":"- Measured water levels for American, Gravelly, and Spanaway Lakes, near the southeastern part of Puget Sound, Washington, 2000–18"},{"id":432075,"rank":9,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2024/5026/v2/data/sir20245026v2_Table1.7.csv","text":"Table 1.7","size":"398 KB","linkFileType":{"id":7,"text":"csv"},"description":"SIR 2024-5026 Vol 2 Table 1.7","linkHelpText":"- Averages of measured hydraulic-head values for selected wells and corresponding simulated steady-state values, near the southeastern part of Puget Sound, Washington, 2005-15"},{"id":432076,"rank":10,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2024/5026/v2/data/sir20245026v2_Table1.8.csv","text":"Table 1.8","size":"291 KB","linkFileType":{"id":7,"text":"csv"},"description":"SIR 2024-5026 Vol 2 Table 1.8","linkHelpText":"- Estimated and simulated monthly average base flow for selected stations, near the southeastern part of Puget Sound, Washington, 2005–15"},{"id":432077,"rank":11,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2024/5026/v2/data/sir20245026v2_Table1.9.csv","text":"Table 1.9","size":"9 KB","linkFileType":{"id":7,"text":"csv"},"description":"SIR 2024-5026 Vol 2 Table 1.9","linkHelpText":"- Estimated and simulated base-flow values for the steady-state model version for stations with continuous records, near the southeastern part of Puget Sound, Washington, 2005–15"},{"id":432078,"rank":12,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2024/5026/v2/data/sir20245026v2_Table1.10.csv","text":"Table 1.10","size":"63 KB","linkFileType":{"id":7,"text":"csv"},"description":"SIR 2024-5026 Vol 2 Table 1.10","linkHelpText":"- Estimated and simulated vertical hydraulic-head differences for the steady-state model version between an upper and lower model layer for selected locations, near the southeastern part of Puget Sound, Washington, 2005–15"},{"id":432080,"rank":14,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2024/5026/v2/data/sir20245026v2_Table1.12.csv","text":"Table 1.12","size":"199 KB","linkFileType":{"id":7,"text":"csv"},"description":"SIR 2024-5026 Vol 2 Table 1.12","linkHelpText":"- Model calibration parameters showing input to the control file for the Model-Independent Parameter Estimation (PEST) program"},{"id":432081,"rank":15,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2024/5026/v2/data/sir20245026v2_Table1.13.csv","text":"Table 1.13","size":"12 KB","linkFileType":{"id":7,"text":"csv"},"description":"SIR 2024-5026 Vol 2 Table 1.13","linkHelpText":"- Simulated groundwater budget for the calibrated transient model version, near the southeastern part of Puget Sound, Washington, 2005–15"},{"id":432083,"rank":17,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2024/5026/v2/data/sir20245026v2_Tables1.1-1.14.xlsx","text":"Tables 1.1-1.14","size":"5.2 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More than 1 million people live within the active model area (AMA) in the southeastern part of the lowlands surrounding Puget Sound, or Puget Lowland, Washington, and groundwater is the source for approximately one-half of their public, domestic, and irrigation water demands. The 887-square-mile AMA, located in King and Pierce Counties, represents the area of analysis for the conceptual hydrogeologic framework and numerical groundwater-flow models within the study area and includes the Puyallup River and Chambers-Clover Creek watersheds. To assess the potential hydrologic and anthropogenic impacts to groundwater and the connected surface-water resources, conceptual and numerical groundwater-flow models of groundwater flow were developed by the U.S. Geological Survey Washington Water Science Center in close cooperation with 18 water-resource agencies and stakeholders.
This report presents information used to characterize the groundwater-flow system and the development of a numerical model in the AMA. Included are descriptions of the geology and conceptual hydrogeologic framework, groundwater levels and flow directions, groundwater recharge and discharge, numerical groundwater-flow model construction and results, and model limitations. The study area encompasses the western part of Pierce County and the southwestern part of King County, Washington. The study area extends south to the Nisqually River, southwest to Tanwax Creek, northeast to the Green River, and north through the valley near Auburn and adjacent uplands. It is bounded on the east by foothills of the Cascade Range, and on the northwest by Puget Sound.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20245026v1","collaboration":"Prepared in cooperation with the Cities of Auburn, Milton, Puyallup, Sumner, and Tacoma; Pierce Conservation District; Pierce County Public Works; Washington State Department of Health; Washington State Department of Ecology; Thurston County Public Utility District; Cascade Water Alliance; Lakehaven Utility District; Lakewood Water District; Firgrove Mutual Water Company; Fruitland Mutual Water Company; Spanaway Water Company; Summit Water & Supply Company; and Mt. View-Edgewood Water Company","usgsCitation":"Welch, W.B., Bright, V.A.L., Gendaszek, A.S., Dunn, S.B., Headman, A.O., and Fasser, E.T., 2024, Conceptual hydrogeologic framework and groundwater budget near the southeastern part of Puget Sound, Washington, v. 1 of Welch, W.B., and Long, A.J., eds., Characterization of groundwater resources near the southeastern part of Puget Sound, Washington, 3 chap. (A–C): U.S. Geological Survey Scientific Investigations Report 2024–5026–A–C, [variously paged; 71 p.], 1 pl., https://doi.org/10.3133/sir20245026v1.","productDescription":"Report: 71 p.; Data Release: 1 Plate: 50.67 × 37.33 inches","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-135626","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":499451,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_117216.htm","linkFileType":{"id":5,"text":"html"}},{"id":432059,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2024/5026/v1/sir20245026v1.jpg"},{"id":432065,"rank":7,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2024/5026/v1/sir20245026v1_plate.pdf","text":"Plate 1","size":"5.51 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2024-5026 Vol 1 Plate 1"},{"id":432064,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2024/5026/v1/sir20245026v1.XML"},{"id":432063,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2024/5026/v1/images"},{"id":433528,"rank":4,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2024/5026/v1/sir20245026v1_versionHist.txt","description":"SIR 2024-5026 Vol 1 Version History"},{"id":432062,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9JFKLMG","text":"USGS data release","description":"USGS data release","linkHelpText":"Spatial data in support of the characterization of water resources near the southeastern part of Puget Sound, Washington"},{"id":432060,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2024/5026/v1/sir20245026v1.pdf","text":"Report","size":"57.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2025-5026 Vol 1"}],"country":"United States","state":"Washington","otherGeospatial":"Puget Sound","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.8989970759464,\n 47.52614250846048\n ],\n [\n -122.8989970759464,\n 46.60885290293453\n ],\n [\n -121.43135900005484,\n 46.60885290293453\n ],\n [\n -121.43135900005484,\n 47.52614250846048\n ],\n [\n -122.8989970759464,\n 47.52614250846048\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Washington Water Science Center
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The partners of the Chesapeake Bay are investing billions of dollars in the restoration of critical habitats to improve conditions for people and living resources throughout the Bay and its watershed. However, the recent proliferation of invasive Ictalurus furcatus (blue catfish) in the Chesapeake Bay’s major rivers has the potential to disrupt these restoration efforts and limit the full potential improvement of the ecosystem. The U.S. Geological Survey can help respond to this management challenge in the Nation’s largest estuary by leveraging its leadership and technical capabilities to work with resource managers, academics, and other stakeholders.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20243033","usgsCitation":"Robertson, E., Malpass, J., Ottinger, C., Griffin, J., Densmore, C., Hyer, K., 2024, Invasive blue catfish in the Chesapeake Bay: A risk to realizing Bay restoration investments: U.S. Geological Survey Fact Sheet 2024–3033, 4 p., https://doi.org/10.3133/fs20243033.","productDescription":"3 p.","numberOfPages":"3","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-169320","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":499129,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_117223.htm","linkFileType":{"id":5,"text":"html"}},{"id":432932,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2024/3033/fs20243033_print.pdf","text":"Report","size":"1.93 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2024-3033","linkHelpText":"Printer-friendly version"},{"id":432930,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2024/3033/coverthb2.jpg"},{"id":432931,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2024/3033/fs20243033.pdf","text":"Report","size":"1.73 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2024-3033"}],"country":"United States","otherGeospatial":"Chesapeake Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -78.96493103491717,\n 40.67063909676753\n ],\n [\n -78.96493103491717,\n 36.23363948406978\n ],\n [\n -74.8780169724172,\n 36.23363948406978\n ],\n [\n -74.8780169724172,\n 40.67063909676753\n ],\n [\n -78.96493103491717,\n 40.67063909676753\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Eastern Ecological Science Center
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Laurel, Maryland 20708
Submerged macrophytes have complex effects on spatiotemporal characteristics of river ecosystems, including trout habitat. We investigated the impact of submerged macrophyte coverage on trout habitat in the Henrys Fork of the Snake River, Idaho, USA. We hypothesized that higher submerged macrophyte coverage would create new habitat types beneficial for trout growth. We assessed river physical and biotic attributes, trout habitat preferences, and estimated trout growth potential with bioenergetics models across a gradient of submerged macrophyte coverage (32–94%). We identified four distinct habitat types within the riverscape shaped by submerged macrophyte coverage. Increased submerged macrophyte coverage increased the frequency of habitat types with higher trout growth potential but reduced the occurrence of preferred habitat types. We observed no relationship between reach-scale trout growth potential and submerged macrophyte coverage. However, an outlier of very high trout growth potential at 94% submerged macrophyte coverage suggests a potential threshold effect. More study is required but our observations suggest macrophyte growth homogenized physical habitat characteristics, reduced flow velocities, and increased invertebrate drift, thereby enhancing trout growth potential. Our findings underscore the complex interplay between submerged macrophytes and trout habitat dynamics across scales, emphasizing the importance of considering both physical and biological effects on trout habitat.
","language":"English","publisher":"Springer","doi":"10.1007/s10750-024-05671-7","usgsCitation":"McLaren, J.S., Van Kirk, R.W., Budy, P., and Brothers, S., 2024, The reach-scale biogeomorphic effect of submerged macrophytes on trout habitat suitability: Hydrobiologia, v. 851, p. 5167-5180, https://doi.org/10.1007/s10750-024-05671-7.","productDescription":"14 p.","startPage":"5167","endPage":"5180","ipdsId":"IP-157131","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":485716,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho","otherGeospatial":"Henrys Fork, Snake River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -111.18272502007463,\n 44.565942435149395\n ],\n [\n -111.69541678783352,\n 44.565942435149395\n ],\n [\n -111.69541678783352,\n 44.271529079239684\n ],\n [\n -111.18272502007463,\n 44.271529079239684\n ],\n [\n -111.18272502007463,\n 44.565942435149395\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"851","noUsgsAuthors":false,"publicationDate":"2024-08-21","publicationStatus":"PW","contributors":{"authors":[{"text":"McLaren, John S.","contributorId":337322,"corporation":false,"usgs":false,"family":"McLaren","given":"John","email":"","middleInitial":"S.","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":936626,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Van Kirk, Robert W.","contributorId":337326,"corporation":false,"usgs":false,"family":"Van Kirk","given":"Robert","email":"","middleInitial":"W.","affiliations":[{"id":81016,"text":"Henrys Fork Foundation","active":true,"usgs":false}],"preferred":false,"id":936627,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Budy, Phaedra E. 0000-0002-9918-1678","orcid":"https://orcid.org/0000-0002-9918-1678","contributorId":228930,"corporation":false,"usgs":true,"family":"Budy","given":"Phaedra E.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":936628,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brothers, Soren","contributorId":339019,"corporation":false,"usgs":false,"family":"Brothers","given":"Soren","email":"","affiliations":[{"id":81013,"text":"Department of Natural History","active":true,"usgs":false}],"preferred":false,"id":936629,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70256874,"text":"sir20245026 - 2024 - Characterization of groundwater resources near the southeastern part of Puget Sound, Washington","interactions":[{"subject":{"id":70256697,"text":"sir20245026v1 - 2024 - Conceptual hydrogeologic framework and groundwater budget near the southeastern part of Puget Sound, Washington","indexId":"sir20245026v1","publicationYear":"2024","noYear":false,"chapter":"A-C","displayTitle":"Conceptual Hydrogeologic Framework and Groundwater Budget Near the Southeastern Part of Puget Sound, Washington","title":"Conceptual hydrogeologic framework and groundwater budget near the southeastern part of Puget Sound, Washington"},"predicate":"IS_PART_OF","object":{"id":70256874,"text":"sir20245026 - 2024 - Characterization of groundwater resources near the southeastern part of Puget Sound, Washington","indexId":"sir20245026","publicationYear":"2024","noYear":false,"title":"Characterization of groundwater resources near the southeastern part of Puget Sound, Washington"},"id":1},{"subject":{"id":70256698,"text":"sir20245026v2 - 2024 - Numerical model of the groundwater-flow system near the southeastern part of Puget Sound, Washington","indexId":"sir20245026v2","publicationYear":"2024","noYear":false,"chapter":"D-E","displayTitle":"Numerical Model of the Groundwater-Flow System Near the Southeastern Part of Puget Sound, Washington","title":"Numerical model of the groundwater-flow system near the southeastern part of Puget Sound, Washington"},"predicate":"IS_PART_OF","object":{"id":70256874,"text":"sir20245026 - 2024 - Characterization of groundwater resources near the southeastern part of Puget Sound, Washington","indexId":"sir20245026","publicationYear":"2024","noYear":false,"title":"Characterization of groundwater resources near the southeastern part of Puget Sound, Washington"},"id":2}],"lastModifiedDate":"2024-09-06T18:14:28.690362","indexId":"sir20245026","displayToPublicDate":"2024-08-21T09:59:52","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":"2024-5026","displayTitle":"Characterization of Groundwater Resources Near the Southeastern Part of Puget Sound, Washington","title":"Characterization of groundwater resources near the southeastern part of Puget Sound, Washington","docAbstract":"More than 1 million people live within the active model area (AMA) in the southeastern part of the lowlands surrounding Puget Sound, or Puget Lowland, Washington, and groundwater is the source for approximately one-half of their public, domestic, and irrigation water demands. The 887-square-mile AMA, located in King and Pierce Counties, represents the area of analysis for the conceptual hydrogeologic framework and numerical groundwater-flow models within the study area and includes the Puyallup River and Chambers-Clover Creek watersheds. To assess the potential hydrologic and anthropogenic impacts to groundwater and the connected surface-water resources, conceptual and numerical groundwater-flow models of groundwater flow were developed by the U.S. Geological Survey Washington Water Science Center in close cooperation with 18 water-resource agencies and stakeholders.
This multichapter volume documents the development of the conceptual and numerical groundwater-flow models of groundwater flow. Chapters A, B, and C provide an overall introduction to the multichapter volume (Chapter A), the conceptual hydrogeologic framework (Chapter B), and the groundwater budget (Chapter C). Chapters D and E describe numerical groundwater-flow model construction and calibration (Chapter D) and the numerical groundwater-flow model results (Chapter E). Collectively, these reports present a characterization and simulation tool for groundwater resources near the southeastern part of Puget Sound, Washington.
","doi":"10.3133/sir20245026","usgsCitation":"Welch, W.B., and Long, A.J., eds., Characterization of groundwater resources near the southeastern part of Puget Sound, Washington: U.S. Geological Survey Scientific Investigations Report 2024–5026, https://doi.org/10.3133/sir20245026.","onlineOnly":"Y","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":433028,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"}],"geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -125.74462161441157,\n 49.512370286103504\n ],\n [\n -125.74462161441157,\n 46.69617446727628\n ],\n [\n -120.97655520816149,\n 46.69617446727628\n ],\n [\n -120.97655520816149,\n 49.512370286103504\n ],\n [\n -125.74462161441157,\n 49.512370286103504\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Washington Water Science Center
U.S. Geological Survey
934 Broadway, Suite 300
Tacoma, Washington 98402
Genetic diversity is essential for maintaining healthy populations and ecosystems. Several approaches have recently been developed to evaluate population genetic trends without necessarily collecting new genetic data. Such “genetic diversity indicators” enable rapid, large-scale evaluation across dozens to thousands of species. Empirical genetic studies, when available, provide detailed information that is important for management, such as estimates of gene flow, inbreeding, genetic erosion and adaptation. In this article, we argue that the development and advancement of genetic diversity indicators is a complementary approach to genetic studies in conservation biology, but not a substitute. Genetic diversity indicators and empirical genetic data can provide different information for conserving genetic diversity. Genetic diversity indicators enable affordable tracking, reporting, prioritization and communication, although, being proxies, do not provide comprehensive evaluation of the genetic status of a species. Conversely, genetic methods offer detailed analysis of the genetic status of a given species or population, although they remain challenging to implement for most species globally, given current capacity and resourcing. We conclude that indicators and genetic studies are both important for genetic conservation actions and recommend they be used in combination for conserving and monitoring genetic diversity.
","language":"English","publisher":"Springer","doi":"10.1007/s10592-024-01632-8","usgsCitation":"Hoban, S.M., Paz-Vinas, I., Shaw, R.E., Castillo-Reina, L., da Silva, J.M., DeWoody, J., Ekblom, R., Fedorca, A., Forester, B.R., Funk, W., Geue, J.C., Heuertz, M., Hollingsworth, P.M., Hughes, A.C., Hunter, M., Hvilsom, C., Ishihama, F., Jordan, R., Kalamujic Stroil, B., Kershaw, F., Khoury, C.K., Koppa, V., Laikre, L., MacDonald, A.J., Mastretta-Yanes, A., Meek, M.H., Mergeay, J., Millette, K.L., O'Brien, D., Rincon-Parra, V.J., Rodriguez-Morales, M., Schuman, M.C., Segelbacher, G., Sunnucks, P., Taylor, R., Thurfjell, H., Vernesi, C., and Grueber, C.E., 2024, DNA-based studies and genetic diversity indicator assessments are complementary approaches to conserving evolutionary potential: Conservation Genetics, v. 25, p. 1147-1153, https://doi.org/10.1007/s10592-024-01632-8.","productDescription":"7 p.","startPage":"1147","endPage":"1153","ipdsId":"IP-160562","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":439203,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10592-024-01632-8","text":"Publisher Index Page"},{"id":433496,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"25","noUsgsAuthors":false,"publicationDate":"2024-08-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Hoban, Sean M. 0000-0002-0348-8449","orcid":"https://orcid.org/0000-0002-0348-8449","contributorId":206582,"corporation":false,"usgs":false,"family":"Hoban","given":"Sean","email":"","middleInitial":"M.","affiliations":[{"id":37343,"text":"The Morton Arboretum","active":true,"usgs":false}],"preferred":false,"id":912310,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Paz-Vinas, Ivan","contributorId":239614,"corporation":false,"usgs":false,"family":"Paz-Vinas","given":"Ivan","email":"","affiliations":[{"id":47934,"text":"Laboratoire Ecologie Fonctionnelle et Environnement, Université de Toulouse","active":true,"usgs":false}],"preferred":false,"id":912311,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shaw, Robyn E.","contributorId":260838,"corporation":false,"usgs":false,"family":"Shaw","given":"Robyn","email":"","middleInitial":"E.","affiliations":[{"id":52690,"text":"Environmental and Conservation Sciences, Murdoch University, Perth, Australia","active":true,"usgs":false}],"preferred":false,"id":912312,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Castillo-Reina, Luis","contributorId":340272,"corporation":false,"usgs":false,"family":"Castillo-Reina","given":"Luis","email":"","affiliations":[{"id":81533,"text":"Department of Biology, Faculty of Science, KU Leuven","active":true,"usgs":false}],"preferred":false,"id":912313,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"da Silva, Jessica M.","contributorId":290139,"corporation":false,"usgs":false,"family":"da Silva","given":"Jessica","email":"","middleInitial":"M.","affiliations":[{"id":62352,"text":"South African National Biodiversity Institute, Kirstenbosch Research Centre, Rhodes Drive, Private Bag X7, 7735 Cape Town, South Africa","active":true,"usgs":false}],"preferred":false,"id":912314,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"DeWoody, J. 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Alejandra","affiliations":[{"id":82257,"text":"Department of Biology, Faculty of Science, Pontificia Universidad Javeriana, Bogotá D.C","active":true,"usgs":false}],"preferred":false,"id":912340,"contributorType":{"id":1,"text":"Authors"},"rank":31},{"text":"Schuman, Meredith C. 0000-0003-3159-3534","orcid":"https://orcid.org/0000-0003-3159-3534","contributorId":343905,"corporation":false,"usgs":false,"family":"Schuman","given":"Meredith","email":"","middleInitial":"C.","affiliations":[{"id":82258,"text":"Spatial Genetics, Remote Sensing Laboratories, Department of Geography, University of Zurich, Zurich, Switzerland","active":true,"usgs":false}],"preferred":false,"id":912341,"contributorType":{"id":1,"text":"Authors"},"rank":32},{"text":"Segelbacher, Gernot","contributorId":206584,"corporation":false,"usgs":false,"family":"Segelbacher","given":"Gernot","email":"","affiliations":[{"id":37345,"text":"University of Freiburg, Germany","active":true,"usgs":false}],"preferred":false,"id":912342,"contributorType":{"id":1,"text":"Authors"},"rank":33},{"text":"Sunnucks, Paul 0000-0002-8139-7059","orcid":"https://orcid.org/0000-0002-8139-7059","contributorId":333555,"corporation":false,"usgs":false,"family":"Sunnucks","given":"Paul","email":"","affiliations":[{"id":27950,"text":"School of Biological Sciences, Monash University","active":true,"usgs":false}],"preferred":false,"id":912343,"contributorType":{"id":1,"text":"Authors"},"rank":34},{"text":"Taylor, Rebecca S. 0000-0002-8916-4858","orcid":"https://orcid.org/0000-0002-8916-4858","contributorId":343906,"corporation":false,"usgs":false,"family":"Taylor","given":"Rebecca S.","affiliations":[{"id":82259,"text":"Landscape Science and Technology Division, Environment and Climate Change Canada, Ottawa, Canada","active":true,"usgs":false}],"preferred":false,"id":912344,"contributorType":{"id":1,"text":"Authors"},"rank":35},{"text":"Thurfjell, Henrik","contributorId":305348,"corporation":false,"usgs":false,"family":"Thurfjell","given":"Henrik","email":"","affiliations":[{"id":66219,"text":"Swedish Species Information Centre, Swedish University of Agricultural Sciences","active":true,"usgs":false}],"preferred":false,"id":912345,"contributorType":{"id":1,"text":"Authors"},"rank":36},{"text":"Vernesi, Cristiano","contributorId":239922,"corporation":false,"usgs":false,"family":"Vernesi","given":"Cristiano","email":"","affiliations":[{"id":48051,"text":"Dept. of Sustainable Agroecosystems and Bioresources, Research and Innovation Centre - Fondazione Edmund Mach","active":true,"usgs":false}],"preferred":false,"id":912346,"contributorType":{"id":1,"text":"Authors"},"rank":37},{"text":"Grueber, Catherine E.","contributorId":239927,"corporation":false,"usgs":false,"family":"Grueber","given":"Catherine","email":"","middleInitial":"E.","affiliations":[{"id":48055,"text":"School of Life and Environmental Sciences, Faculty of Science, The University of Sydney","active":true,"usgs":false}],"preferred":false,"id":912347,"contributorType":{"id":1,"text":"Authors"},"rank":38}]}} ,{"id":70257760,"text":"70257760 - 2024 - Despite regional variation, Gymnorhinus cyanocephalus (Pinyon Jay) densities generally increase with local pinyon–juniper cover and heterogeneous ground cover","interactions":[],"lastModifiedDate":"2024-12-26T16:34:01.74251","indexId":"70257760","displayToPublicDate":"2024-08-21T07:21:56","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9101,"text":"Ornithological Applications","printIssn":"0010-5422","active":true,"publicationSubtype":{"id":10}},"title":"Despite regional variation, Gymnorhinus cyanocephalus (Pinyon Jay) densities generally increase with local pinyon–juniper cover and heterogeneous ground cover","docAbstract":"Traditionally, local-scale habitat-relationship models are developed over small spatial extents, limiting model transferability and inference outside the study area. Thus, habitat managers frequently lack fine-scale information regarding the influence of vegetation composition and structure on site suitability or species abundance. Gymnorhinus cyanocephalus (Pinyon Jay) represents one declining species for which managers have limited information regarding the influence that vegetation composition and structure have on abundance at broad scales. To address this need, we developed a hierarchical Bayesian abundance model using summertime bird and vegetation data collected under the Integrated Monitoring in Bird Conservation Regions program to explain jay abundance as a function of local conditions. Our G. cyanocephalus abundance model allowed abundance relationships with pinyon pine (Pinus edulis and P. monophylla) and juniper (Juniperus spp.) to vary by ecoregion, thereby accounting for potential regional differences in habitat associations. We found G. cyanocephalus abundance was generally positively associated with pinyon pine and juniper cover; however, habitat relationships varied by ecoregion. Additionally, we found positive associations between jay abundance and grass cover, sagebrush cover, and percent bare ground. Our results agree with prior research suggesting mechanical removal of pinyon pine and juniper trees for sagebrush restoration or fuel treatments may negatively affect G. cyanocephalus. Managers wishing to reduce pinyon and juniper tree cover without negatively affecting G. cyanocephalus may benefit from targeting sites where both large-scale distribution models and our local habitat relationships suggest G. cyanocephalus are likely to occur in low numbers. Additionally, our modeled relationships indicate restoration that increases grass cover, sagebrush cover, and bare ground, while maintaining pinyon and (or) juniper cover, may lead to increased local densities of G. cyanocephalus.
","language":"English","publisher":"Oxford University Press","doi":"10.1093/ornithapp/duae036","usgsCitation":"Van Lanen, N.J., Monroe, A., and Aldridge, C.L., 2024, Despite regional variation, Gymnorhinus cyanocephalus (Pinyon Jay) densities generally increase with local pinyon–juniper cover and heterogeneous ground cover: Ornithological Applications, v. 126, no. 4, duae036, https://doi.org/10.1093/ornithapp/duae036.","productDescription":"duae036","ipdsId":"IP-158852","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":439204,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/ornithapp/duae036","text":"Publisher Index Page"},{"id":433154,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"126","issue":"4","noUsgsAuthors":false,"publicationDate":"2024-08-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Van Lanen, Nicholas J. 0000-0003-0871-0261","orcid":"https://orcid.org/0000-0003-0871-0261","contributorId":302927,"corporation":false,"usgs":true,"family":"Van Lanen","given":"Nicholas","email":"","middleInitial":"J.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":911621,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Monroe, Adrian P. 0000-0003-0934-8225 amonroe@usgs.gov","orcid":"https://orcid.org/0000-0003-0934-8225","contributorId":152209,"corporation":false,"usgs":true,"family":"Monroe","given":"Adrian P.","email":"amonroe@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":911622,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":911623,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70257808,"text":"70257808 - 2024 - On the uncertain intensity estimate of the 1859 Carrington storm","interactions":[],"lastModifiedDate":"2024-08-28T11:58:46.249223","indexId":"70257808","displayToPublicDate":"2024-08-21T06:57:28","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":18352,"text":"Journal of Space Weather and Space Climate","active":true,"publicationSubtype":{"id":10}},"title":"On the uncertain intensity estimate of the 1859 Carrington storm","docAbstract":"A study is made of the intensity of the Carrington magnetic storm of September 1859 as inferred from visual measurements of horizontal-component geomagnetic disturbance made at the Colaba observatory in India. Using data from modern observatories, a lognormal statistical model of storm intensity is developed, to characterize the maximum-negative value of the storm-time disturbance index (maximum –Dst) versus geomagnetic disturbance recorded at low-latitude observatories during magnetic storms. With this model and a recently published presentation of the Colaba data, the most likely maximum –Dst of the Carrington storm and its credibility interval are estimated. A related model is used to examine individual Colaba disturbance values reported for the Carrington storm. Results indicate that only about one in a million storms with maximum –Dst like the Carrington storm would result in local disturbance greater than that reported from Colaba. This indicates that either the Colaba data were affected by magnetospheric-ionospheric current systems in addition to the ring current, or there might be something wrong with the Colaba data. If the most extreme Colaba disturbance value is included in the analysis, then, of all hypothetical storms generating the hourly average disturbance recorded at Colaba during the Carrington storm, the median maximum –Dst = 964 nT, with a 68% credibility interval of [855,1087] nT. If the most extreme Colaba disturbance value is excluded from the analysis, then the median maximum –Dst = 866 nT, with a 68% credibility interval of [768,977] nT. The widths of these intervals indicate that estimates of the occurrence frequency of Carrington-class storms are very uncertain, as are related estimates of risk for modern technological systems.
","language":"English","publisher":"EcoSciences","doi":"10.1051/swsc/2024015","usgsCitation":"Love, J.J., Rigler, E.J., Hayakawa, H., and Mursula, K., 2024, On the uncertain intensity estimate of the 1859 Carrington storm: Journal of Space Weather and Space Climate, v. 14, https://doi.org/10.1051/swsc/2024015.","productDescription":"21, 16 p.","startPage":"21","ipdsId":"IP-153188","costCenters":[{"id":78686,"text":"Geologic Hazards Science Center - Seismology / Geomagnetism","active":true,"usgs":true}],"links":[{"id":439205,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1051/swsc/2024015","text":"External Repository"},{"id":433242,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"14","noUsgsAuthors":false,"publicationDate":"2024-08-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Love, Jeffrey J. 0000-0002-3324-0348 jlove@usgs.gov","orcid":"https://orcid.org/0000-0002-3324-0348","contributorId":760,"corporation":false,"usgs":true,"family":"Love","given":"Jeffrey","email":"jlove@usgs.gov","middleInitial":"J.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":911733,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rigler, E. Joshua 0000-0003-4850-3953 erigler@usgs.gov","orcid":"https://orcid.org/0000-0003-4850-3953","contributorId":4367,"corporation":false,"usgs":true,"family":"Rigler","given":"E.","email":"erigler@usgs.gov","middleInitial":"Joshua","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":911734,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hayakawa, H. 0000-0001-5370-3365","orcid":"https://orcid.org/0000-0001-5370-3365","contributorId":261775,"corporation":false,"usgs":false,"family":"Hayakawa","given":"H.","email":"","affiliations":[{"id":53009,"text":"Nagoya University, Rutherford Appleton Laboratory, Nishina Center","active":true,"usgs":false}],"preferred":false,"id":911735,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mursula, Kalevi 0000-0003-4892-5056","orcid":"https://orcid.org/0000-0003-4892-5056","contributorId":343695,"corporation":false,"usgs":false,"family":"Mursula","given":"Kalevi","email":"","affiliations":[{"id":82163,"text":"Oulu University","active":true,"usgs":false}],"preferred":false,"id":911736,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70257626,"text":"ofr20241036 - 2024 - Airborne lidar accuracy analysis for dual photogrammetric and lidar sensor pilot project in Colorado, 2019","interactions":[],"lastModifiedDate":"2026-01-29T19:50:12.601231","indexId":"ofr20241036","displayToPublicDate":"2024-08-20T16:19:54","publicationYear":"2024","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2024-1036","displayTitle":"Airborne Lidar Accuracy Analysis for Dual Photogrammetric and Lidar Sensor Pilot Project in Colorado, 2019","title":"Airborne lidar accuracy analysis for dual photogrammetric and lidar sensor pilot project in Colorado, 2019","docAbstract":"This report presents accuracy assessment results of the light detection and ranging (lidar) data collected in Colorado during a pilot project in fall 2019. The purpose of the pilot project was to assess the accuracy of lidar and imagery data collected simultaneously for the U.S. Department of Agriculture (USDA) National Agriculture Imagery Program and the U.S. Geological Survey National Geospatial Program 3D Elevation Program (3DEP). A multiagency group consisting of U.S. Department of the Interior agencies and USDA agencies participated in the effort. Department of the Interior agencies included Bureau of Land Management, National Park Service, and U.S. Geological Survey; USDA agencies included the Farm Services Agency, the Natural Resource Conservation Service, and U.S. Forest Service. This pilot project was designed to help determine if a lidar sensor system has the potential to meet future 3DEP topographic lidar collection requirements, ideally at the same altitudes and leaf-on times that National Agriculture Imagery Program is flown.
The airborne sensor system from Leica Geosystems (part of Hexagon) (hereafter referred to as dual sensor system) was used in the pilot project and can collect imagery and three-dimensional point cloud data concurrently. This report examines the characteristics of lidar data from a geometric accuracy perspective. Field surveys were performed to evaluate the three-dimensional absolute and relative accuracy of the airborne lidar data and to determine if the data met 3DEP specifications.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20241036","usgsCitation":"Sampath, A., Irwin, J., and Kim, M., 2024, Airborne lidar accuracy analysis for dual photogrammetric and lidar sensor pilot project in Colorado, 2019: U.S. Geological Survey Open-File Report 2024–1036, 22 p., https://doi.org/10.3133/ofr20241036.","productDescription":"Report: v, 22 p.; Data Release","ipdsId":"IP-145014","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":499258,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_117220.htm","linkFileType":{"id":5,"text":"html"}},{"id":432948,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20241036/full"},{"id":432946,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2024/1036/ofr20241036.XML"},{"id":432945,"rank":3,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2024/1036/images/"},{"id":432944,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2024/1036/ofr20241036.pdf","text":"Report","size":"4.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2024–1036"},{"id":432943,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2024/1036/coverthb.jpg"},{"id":432947,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9CPDWUU","text":"USGS data release","linkHelpText":"Hybrid lidar/imagery sensor validation survey data, 2019"}],"country":"United States","state":"Colorado","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -105.41673062084341,\n 40.689427754445916\n ],\n [\n -105.41673062084341,\n 40.45990268267724\n ],\n [\n -104.91983118255482,\n 40.45990268267724\n ],\n [\n -104.91983118255482,\n 40.689427754445916\n ],\n [\n -105.41673062084341,\n 40.689427754445916\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -106.24129047491809,\n 40.22901702069382\n ],\n [\n -106.24129047491809,\n 39.9645466499631\n ],\n [\n -105.60981370231355,\n 39.9645466499631\n ],\n [\n -105.60981370231355,\n 40.22901702069382\n ],\n [\n -106.24129047491809,\n 40.22901702069382\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Earth Resources Observation and Science Center
U.S. Geological Survey
47914 252nd Street
Sioux Falls, SD 57198
Surveys for the endangered Southwestern Willow Flycatcher (Empidonax traillii extimus) were done at Marine Corps Base Camp Pendleton (MCBCP or “Base”), California, between May 9 and July 20, 2022. All of MCBCP’s historically occupied riparian habitat (core survey area) was surveyed for flycatchers in 2022. None of the non-core survey area was surveyed in 2022.
Eight transient Willow Flycatchers of unknown subspecies were observed on three of the five drainages surveyed in 2022. Willow Flycatchers were not detected at Fallbrook or Pilgrim Creeks. Transients occurred in a range of habitat types, including mixed willow (Salix spp.) riparian, riparian scrub, and upland scrub habitat. Exotic vegetation, primarily poison hemlock (Conium maculatum), was present in most of the flycatcher locations.
In 2022, for the second time since monitoring began in 2000, resident Southwestern Willow Flycatchers were not detected on Base. The decline was not isolated to MCBCP; similar declines have been documented across California in recent years.
The one uniquely banded adult female flycatcher present during the 2021 breeding season did not return to MCBCP in 2022. None of the transients observed during surveys were seen to carry bands.
From 2000 to 2022, adult annual survival of Southwestern Willow Flycatchers on MCBCP was 60±3 percent, whereas first-year survival was 20±3 percent.
A conspecific attraction study was initiated on Base in 2018 and repeated annually through 2022; flycatchers were not observed near automated playback units in 2022.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231080","collaboration":"Prepared in cooperation with Assistant Chief of Staff, Environmental Security, U.S. Marine Corps Base Camp Pendleton","programNote":"Ecosystems Mission Area—Species Management Research Program","usgsCitation":"Howell, S.L., and Kus, B.E., 2024, Distribution, abundance, and breeding activities of the Southwestern Willow Flycatcher at Marine Corps Base Camp Pendleton, California—2022 annual report: U.S. Geological Survey Open-File Report 2023–1080, 27 p., https://doi.org/10.3133/ofr20231080.","productDescription":"vi, 27 p.","numberOfPages":"27","onlineOnly":"Y","ipdsId":"IP-147621","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":423448,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20231080/full"},{"id":423447,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1080/images"},{"id":423446,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2023/1080/ofr20231080.xml","size":"200 KB","linkFileType":{"id":8,"text":"xml"}},{"id":423445,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1080/ofr20231080.pdf","text":"Report","size":"7 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":423444,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1080/covrthb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Marine Corps Base Camp Pendleton","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -117.97155578495742,\n 33.68843828437876\n ],\n [\n -117.97155578495742,\n 33.07385423406275\n ],\n [\n -116.90578319960974,\n 33.07385423406275\n ],\n [\n -116.90578319960974,\n 33.68843828437876\n ],\n [\n -117.97155578495742,\n 33.68843828437876\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819
The purpose of this report is to provide the Marine Corps with an annual summary of abundance, breeding activity, demography, and habitat use of the endangered Southwestern Willow Flycatcher (Empidonax traillii extimus) at Marine Corps Base Camp Pendleton (MCBCP). Surveys for the flycatcher were completed at MCBCP between May 5 and July 31, 2021. All of MCBCP’s historically occupied riparian habitat (core survey area) was surveyed for flycatchers in 2021. Additionally, one-fifth of the non-historically occupied riparian habitat (non-core survey area C) was surveyed for flycatchers. Twenty-four transient Willow Flycatchers of unknown subspecies were observed on five of the seven drainages surveyed in 2021. No Willow Flycatchers were detected at French or Las Flores Creeks. Transients occurred in a range of habitat types, including mixed willow (Salix spp.) riparian, riparian scrub, willow-sycamore (Platanus sp.) dominated or oak (Quercus spp.) sycamore-dominated riparian, and non-native-dominated riparian habitat. Exotic vegetation, primarily poison hemlock (Conium maculatum), was present in most flycatcher locations.
The resident population of Southwestern Willow Flycatchers on MCBCP declined 50 percent, from two individuals in 2020 to one individual in 2021. In 2021, the resident Southwestern Willow Flycatcher population on MCBCP consisted of one unpaired female occupying one territory. No males were observed in 2021. The resident flycatcher population was restricted to the Santa Margarita River, and distribution was limited to the Pueblitos breeding area. The resident flycatcher territory was located in mixed willow riparian habitat.
Nesting was initiated in late May and continued into late July. Two nesting attempts were documented, neither of which were successful. Infertile eggs likely accounted for both nest failures. No instances of Brown-headed Cowbird (Molothrus ater) parasitism were observed. The female flycatcher placed her nests in native sandbar willow (Salix exigua) and used the same nest location for both nesting attempts.
Of resident birds that were present at MCBCP in 2021, 100 percent were banded in previous years; no unbanded birds were detected. Of the two uniquely banded adult flycatchers (one male, one female) present during the 2020 breeding season, 50 percent (one female) returned to MCBCP in 2021. The banded female returned to the same breeding area and territory she occupied in 2020. Neither of the two nestlings banded in 2020 returned to MCBCP in 2021, and neither were detected off Base. From 2000 to 2021, adult over-winter survival of Southwestern Willow Flycatchers on MCBCP was 60±3 percent (mean±standard error [SE]), and first-year survival was 20±3 percent.
A conspecific attraction study that used automatic playback units to broadcast flycatcher vocalizations in order to encourage flycatchers to settle on MCBCP was initiated in 2018 and repeated annually through 2021. The single resident flycatcher (female) detected in 2021 settled close to an automated playback unit.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20241039","collaboration":"Prepared in cooperation with Assistant Chief of Staff, Environmental Security, U.S. Marine Corps Base Camp Pendleton","programNote":"Ecosystems Mission Area—Species Management Research Program","usgsCitation":"Howell, S.L., and Kus, B.E., 2024, Distribution, abundance, and breeding activities of the Southwestern Willow Flycatcher at Marine Corps Base Camp Pendleton, California—2021 annual report: U.S. Geological Survey Open-File Report 2024–1039, 35 p., https://doi.org/10.3133/ofr20241039.","productDescription":"viii, 35 p.","numberOfPages":"35","onlineOnly":"Y","ipdsId":"IP-156551","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":432891,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2024/1039/covrthb.jpg"},{"id":432892,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2024/1039/ofr20241039.pdf","text":"Report","size":"15 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":432893,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2024/1039/ofr20241039.xml"},{"id":432894,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2024/1039/images"},{"id":432895,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20241039/full"}],"country":"United States","state":"California","otherGeospatial":"Marine Corps Base Camp Pendleton","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -117.79672069647273,\n 33.56385799493502\n ],\n [\n -117.79672069647273,\n 33.155239670288594\n ],\n [\n -117.12032821171901,\n 33.155239670288594\n ],\n [\n -117.12032821171901,\n 33.56385799493502\n ],\n [\n -117.79672069647273,\n 33.56385799493502\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819
The U.S. Geological Survey has developed a transient, groundwater-flow model that simulates hydrologic conditions in the Long Island aquifer system as part of an ongoing (since 2016) multiyear, cooperative investigation with the New York State Department of Environmental Conservation. The goals of this investigation are to assist stakeholders and resource managers to evaluate the response of the hydrologic system to changes in future hydraulic stresses. Responses in the hydrologic system include changes in water levels in the hydrogeologic units; discharge to streams, coastal waters, and subsurface infrastructure; and the extent of saline groundwater in the aquifers. Hydraulic stresses include future water-supply management and changes in land use and infrastructure.
The numerical model synthesizes a diverse set of physiographic, geologic, climatic, land-use, and historical population, water use, and infrastructure data to physically represent the Long Island aquifer system from land surface to bedrock and to simulate annual hydrologic conditions between 1900 and 2019. A three-dimensional hydrogeologic framework was developed from existing and recently collected borehole geologic and geophysical data collected as part of a companion drilling program. Water-transmitting properties of the principal aquifer sediments were defined in three dimensions from new and existing lithologic logs. The distribution of recharge from precipitation was estimated from landscape characteristics and climate data. Anthropogenic recharge from wastewater, leaky infrastructure, and storm runoff were estimated from population, infrastructure, and pumping data.
Water-use data, including well locations, depths, and pumping rates, were obtained from historical sources and records and used to estimate pumping stresses continuously in time and space, at an annual average time scale. The data were incorporated into a three-dimensional numerical model using the U.S. Geological Survey finite difference modeling code MODFLOW 6; the model encompassed all of Long Island and surrounding surface waters and simulated historical hydrologic conditions from 1900 to 2019.
The calibration process involved trial and error adjustments using prior knowledge to improve general fit to observations followed by an inverse calibration to update and optimize input parameters, using an iterative ensemble smoother algorithm implemented in PEST++ version 5.0. This resulted in a model that generally was in good agreement with observed, dynamically varying hydrologic conditions from 1900 to 2019. The calibrated model was used to develop two base-case models for scenario testing of future, hypothetical conditions where one represented average-annual conditions, and one represented average-seasonal conditions from 2010 to 2019. The model representing average-annual conditions was modified further to represent an alternate sea-level position of 6 feet above the North American Vertical Datum of 1988, and the model representing average-seasonal conditions was modified to represent the average seasonal effects of a 5-year drought imposed upon current hydrologic conditions.
Recharge is the sole source of water to the aquifer system; groundwater discharges to coastal water and streams and is withdrawn by pumped wells. Model-estimated annual recharge ranged from about 11 inches in 1965 to 41 inches in 1983. On average, from 2010 to 2019, about 23 percent of water was pumped from wells, and about 47 and 27 percent discharged to coastal waters and streams, respectively; the remaining 4 percent was water that moved into storage in the aquifer matrix.
Water levels on Long Island vary naturally during time in response to changes in recharge; the amount of variation is largest in the interior of the island, in areas with highest water table altitudes near groundwater divides and lowest near streams and the coastal waters. The total range of water table altitudes on Long Island between 1900 and 2019 ranged from near 0 to more than 70 feet in western parts of Long Island. The largest range in altitudes is in New York City and is associated with areas of large historical withdrawals between the 1920s and the late 1980s. Water table altitudes generally varied by less than 10 feet in eastern Suffolk County, where the aquifer is under more natural conditions.
Saltwater intrusion is of great concern on Long Island, particularly in western Long Island where both the unconfined and confined parts of the aquifer system have been intruded in response to large-scale groundwater withdrawals; however, the volume of freshwater in the islandwide aquifer system only has changed by about 5 percent between 1900 and 2019. The decadal change in the freshwater volume was largest during the early and mid-20th century, corresponding to the largest historical pumping, but that volume change did not exceed 1 percent.
The negligible change in freshwater volume suggests that saltwater intrusion as of 2019 was limited at an islandwide scale but continues to occur in local areas of Queens and Nassau Counties, adversely affecting current water supplies and limiting future water supplies for affected communities. The regional groundwater model developed for this investigation is a tool that can be used to help determine the viability of current and future water supplies at a regional scale and can be used to support development of additional models at finer scale to support more focused assessments of groundwater sustainability.
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New York Water Science Center
U.S. Geological Survey
425 Jordan Road
Troy, NY 12180–8349
In 2016, the U.S. Geological Survey began a multiyear cooperative study with the New York State Department of Environmental Conservation to evaluate the sustainability of Long Island’s sole-source aquifer system through hydrogeologic mapping, compilation of groundwater chloride concentrations, and groundwater flow modeling. In the initial phase of the islandwide study, the hydrogeologic framework and extent of saltwater intrusion in aquifers in Kings, Queens, and Nassau Counties on western Long Island, N.Y., were investigated. The aquifer system underlying western Long Island has been under stress from pumping of public, irrigation (golf course), and industrial supply wells. Saltwater intrusion has occurred from surrounding embayments (East River, Long Island Sound, Jamaica Bay, and the Atlantic Ocean) due to pumping.
Eighteen boreholes were drilled and cores taken during 2019–21 to collect hydrogeologic, geochemical, and geophysical data to delineate the complex subsurface hydrogeology and extent of saltwater intrusion within the study area. Evaluation of the new cores, reexamination of legacy core descriptions, and analysis of borehole geophysical logs was used to refine the previously published hydrogeologic framework of Pleistocene and Cretaceous unconsolidated sediments in the area, including delineation of a previously undefined hydrogeologic unit between the Magothy aquifer and the Raritan confining unit, herein named the “upper Raritan aquifer.” The upper Raritan aquifer was first recognized in southeastern Nassau County from an analysis of about 50 closely spaced boreholes with high-resolution core descriptions and gamma-ray (gamma) logs. Further analysis of borehole logs across the study area indicated that the upper Raritan aquifer was also present in Kings and Queens Counties.
Nuclear magnetic resonance (NMR) logging was used for the first time on Long Island to provide estimates of the hydraulic properties of the major aquifer and confining units. Unlike other geophysical logs that record responses to the rock matrix and fluid properties and are strongly dependent on mineralogy, NMR logs record responses to the presence of hydrogen protons in the formation fluid to determine water fraction and pore-size distribution. NMR log analysis provided estimates of the clay-bound, capillary-bound, and mobile water fractions and hydraulic conductivity of aquifers and confining units penetrated by five wells in Nassau County.
Pumpage for public-supply and industrial wells on Long Island began in the 1870s with small, localized suppliers of populated areas in Kings and Queens Counties. By 1904–16, pumpage for public water supply in Kings County averaged 21 million gallons per day, and averaged 37 million gallons per day in Queens County, mostly from the upper glacial aquifer. Saltwater intrusion was reported as early as the beginning of the 20th century and included the upper glacial-Jameco-Magothy and Lloyd-North Shore aquifer systems. By 1936, pumping in central Kings County created a major cone of depression in the water table extending to the south shore of much of Kings County and into southwestern Queens County. Saltwater intrusion has caused the shutdown of public-supply wells in Kings, Queens, and Nassau Counties. A large saltwater intrusion wedge in the Lloyd aquifer was indicated in southern Queens County in the early part of the 20th century, and the saltwater interface may have been onshore predevelopment. Most of Kings and Queens Counties are intruded with saltwater in both the upper glacial-Jameco-Magothy and Lloyd-North Shore aquifers systems. Saltwater increased during the 20th century and continues to increase to the present (2023) in the Lloyd-North Shore aquifer system in Great Neck and Manhasset Neck in northern Nassau County. A major wedge of saltwater intrusion in the upper glacial-Jameco-Magothy aquifer in southwestern Nassau County appears to be increasing.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20245048","collaboration":"Prepared in cooperation with the New York State Department of Environmental Conservation","usgsCitation":"Stumm, F., Finkelstein, J.S., Williams, J.H., and Lange, A.D., 2024, Hydrogeologic framework and extent of saltwater intrusion in Kings, Queens, and Nassau Counties, Long Island, New York: U.S. Geological Survey Scientific Investigations Report 2024–5048, 83 p., https://doi.org/10.3133/sir20245048.","productDescription":"Report: ix, 83 p.; 3 Data Releases; Interactive Geospatial Data Viewer","numberOfPages":"83","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-147125","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":431252,"rank":8,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P97WN72B","text":"USGS data release","linkHelpText":"Hydrogeologic framework and 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New York Water Science Center
U.S. Geological Survey
425 Jordan Road
Troy, NY 12180–8349
DNA metabarcoding is a rapidly advancing tool for diet assessment in wildlife ecology. Studies have used a variety of field collection methods to evaluate diet; however, there is a pressing need to understand the differences among sampling methods and the downstream inferential consequences they may have on our ability to document diet accurately and efficiently. We evaluated seven DNA metabarcoding sampling methods to assess the diet of a large avian predator: Buteo lagopus (rough-legged hawk). We collected beak swabs, talon swabs, cheek (buccal) swabs, cloacal swabs, and cloacal loops from captured birds, and collected fecal samples from both captured and uncaptured birds. We described and compared variation in prey recovery within and among the seven sampling methods and identified appropriate analytical methods to compare diet among individuals sampled via different methods. Beak and talon swabs produced the highest prey detection rates, yielded the greatest prey richness per sample, and contributed the most to an individual's total prey richness per sampling occasion compared to other sampling methods. Within individuals sampled using five methods during a single capture occasion, cloacal swabs and cheek swabs positively predicted prey richness and average prey mass, respectively, from fecal samples. While all methods identified similar dominant prey taxa that were consistent with prior diet studies, beak and talon swabs detected greater prey richness at both the individual and population levels. We propose a food residue duration hypothesis whereby methods which sample areas containing food DNA consumed from longer and more continuous pre-sampling time intervals explain variation among sampling methods in observed prey richness. Choice of sampling method can influence predator diet characterization and is particularly important if researchers wish to quantify uncommon diet items or compare diet metrics using samples collected via different methods.
","language":"English","publisher":"Wiley","doi":"10.1002/edn3.70000","usgsCitation":"Paprocki, N., Blair, S., Conway, C.J., Adams, J., Nerkowski, S.A., Kidd, J., and Waits, L., 2024, Comparison of seven DNA metabarcoding sampling methods to assess diet in a large avian predator: Environmental DNA, v. 6, no. 4, e70000, 12 p., https://doi.org/10.1002/edn3.70000.","productDescription":"e70000, 12 p.","ipdsId":"IP-160257","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":490118,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/edn3.70000","text":"Publisher Index Page"},{"id":485837,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"6","issue":"4","noUsgsAuthors":false,"publicationDate":"2024-08-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Paprocki, Neil","contributorId":354983,"corporation":false,"usgs":false,"family":"Paprocki","given":"Neil","affiliations":[{"id":36394,"text":"University of Idaho","active":true,"usgs":false}],"preferred":false,"id":936745,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Blair, Shannon","contributorId":354984,"corporation":false,"usgs":false,"family":"Blair","given":"Shannon","affiliations":[{"id":36394,"text":"University of Idaho","active":true,"usgs":false}],"preferred":false,"id":936746,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":936747,"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":936748,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Nerkowski, Stacey A.","contributorId":338441,"corporation":false,"usgs":false,"family":"Nerkowski","given":"Stacey","email":"","middleInitial":"A.","affiliations":[{"id":36394,"text":"University of Idaho","active":true,"usgs":false}],"preferred":false,"id":936749,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kidd, Jeff W","contributorId":243473,"corporation":false,"usgs":false,"family":"Kidd","given":"Jeff W","affiliations":[],"preferred":false,"id":936750,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Waits, Lisette","contributorId":189210,"corporation":false,"usgs":false,"family":"Waits","given":"Lisette","affiliations":[],"preferred":false,"id":936751,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70267317,"text":"70267317 - 2024 - Landscape-scale modeling to forecast fluvial-aeolian sediment connectivity in river valleys","interactions":[],"lastModifiedDate":"2025-05-20T15:16:10.250817","indexId":"70267317","displayToPublicDate":"2024-08-20T10:08:58","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Landscape-scale modeling to forecast fluvial-aeolian sediment connectivity in river valleys","docAbstract":"Sedimentary landforms on Earth and other planetary bodies are built through scour, transport, and deposition of sediment. Sediment connectivity refers to the hypothesis that pathways of sediment transport do not occur in isolation, but rather are mechanistically linked. In dryland river systems, one such example of sediment connectivity is the transport of fluvially deposited sediment by wind. However, predictive tools that can forecast fluvial-aeolian sediment connectivity at meaningful scales are rare. Here we develop a suite of models for quantifying the availability of river-sourced sediment for aeolian transport as a function of river flow, wind regime, and land cover across 168 km of the Colorado River in Grand Canyon, USA. We compare and validate these models using topographic changes observed over 10 years in a coupled river sandbar-aeolian dunefield setting. The models provide a path forward for directly linking fluvial hydrology with the management and understanding of aeolian landscapes.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2024GL110106","usgsCitation":"Kasprak, A., Sankey, J., and Caster, J., 2024, Landscape-scale modeling to forecast fluvial-aeolian sediment connectivity in river valleys: Geophysical Research Letters, v. 51, no. 6, e2024GL110106, 10 p., https://doi.org/10.1029/2024GL110106.","productDescription":"e2024GL110106, 10 p.","ipdsId":"IP-165471","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":490135,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2024gl110106","text":"Publisher Index Page"},{"id":486217,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Grand Canyon National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -111.41686436104216,\n 36.95682017793375\n ],\n [\n -112.32831221274077,\n 36.95682017793375\n ],\n [\n -112.32831221274077,\n 36.00005971677052\n ],\n [\n -111.41686436104216,\n 36.00005971677052\n ],\n [\n -111.41686436104216,\n 36.95682017793375\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"51","issue":"6","noUsgsAuthors":false,"publicationDate":"2024-08-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Kasprak, Alan 0000-0001-8184-6128","orcid":"https://orcid.org/0000-0001-8184-6128","contributorId":245742,"corporation":false,"usgs":false,"family":"Kasprak","given":"Alan","affiliations":[{"id":49307,"text":"Current: Utah State University. 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Topics included development of wildlife health information management systems, analysis of the current surveillance network, development of a Theory of Change for a strengthened surveillance network, planning workshops to create a wildlife health network, training on wildlife disease outbreak investigation and field sample collection, leading networks, and individual training on bioinformatics and laboratory techniques. Engagement of stakeholders at all levels, continuous communication throughout the project, use of both strategic planning tools and pedagogical methods, and using iterative and adaptive approaches, were key factors to the success of this project.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/fvets.2024.1462280","usgsCitation":"Suwanpakdee, S., Sangkachai, N., Wiratsudakul, A., Wiriyarat, W., Sakcamduang, W., Wongluechai, P., Pabutta, C., Sariya, L., Korkijthamkul, W., Blehert, D.S., White, C.L., Walsh, D.P., Stephen, C., Ratanakorn, P., and Sleeman, J.M., 2024, Wildlife health capacity enhancement in Thailand through the World Organisation for Animal Health Twinning Program: Frontiers in Veterinary Science, v. 11, 1462280, 11 p., https://doi.org/10.3389/fvets.2024.1462280.","productDescription":"1462280, 11 p.","ipdsId":"IP-164114","costCenters":[{"id":399,"text":"Montana Cooperative Wildlife Research Unit","active":false,"usgs":true},{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true},{"id":82110,"text":"Midcontinent Regional Director's Office","active":true,"usgs":true}],"links":[{"id":439206,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index 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