{"pageNumber":"142","pageRowStart":"3525","pageSize":"25","recordCount":40783,"records":[{"id":70239230,"text":"70239230 - 2023 - Empirical evidence for effects of invasive American Bullfrogs on occurrence of native amphibians and emerging pathogens","interactions":[],"lastModifiedDate":"2023-03-24T16:23:30.181101","indexId":"70239230","displayToPublicDate":"2022-12-08T07:20:55","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"Empirical evidence for effects of invasive American Bullfrogs on occurrence of native amphibians and emerging pathogens","docAbstract":"<p>Invasive species and emerging infectious diseases are two of the greatest threats to biodiversity. American Bullfrogs (<i>Rana</i><span>&nbsp;</span>[<i>Lithobates</i>]<span>&nbsp;</span><i>catesbeiana</i>), which have been introduced to many parts of the world, are often linked with declines of native amphibians via predation and spreading emerging pathogens such as amphibian chytrid fungus (<i>Batrachochytrium dendrobatidis</i><span>&nbsp;</span>[Bd]) and ranaviruses. Although many studies have investigated the potential role of bullfrogs in declines of native amphibians, analyses that account for shared habitat affinities and imperfect detection have found limited support for clear effects. Similarly, the role of bullfrogs in shaping the patch-level distribution of pathogens is unclear. We used eDNA methods to sample 233 sites in the southwestern USA and Sonora, Mexico (2016–2018) to estimate how presence of bullfrogs affects occurrence of 4 native amphibians, Bd, and ranaviruses. Based on 2-species, dominant-subordinate occupancy models fitted in a Bayesian context, federally threatened Chiricahua Leopard Frogs (<i>R. chiricahuensis</i>) and Western Tiger Salamanders (<i>Ambystoma mavortium</i>) were 8 times (32% vs. 4%) and 2 times (36% vs. 18%), respectively, less likely to occur at sites where bullfrogs occurred. Evidence for negative effects of bullfrogs on Lowland Leopard Frogs (<i>R. yavapaiensis</i>) and Northern Leopard Frogs (<i>R. pipiens</i>) was less clear, possibly because of smaller numbers of sites where these native species still occur and because bullfrogs often occur at lower densities in streams, the primary habitat for Lowland Leopard Frogs. At the community level, Bd was most likely to occur where bullfrogs co-occurred with native amphibians, which could increase risk to native species. Ranaviruses were estimated to occur at 33% of bullfrog-only sites, 10% of sites where bullfrogs and native amphibians co-occurred, and only 3% of sites where only native amphibians occurred. Of the 85 sites where we did not detect any of the 5 target amphibian species, we also did not detect Bd or ranaviruses; this suggests other hosts do not drive the distribution of these pathogens in our study area. Our results provide landscape-scale evidence that bullfrogs reduce occurrence of native amphibians and increase occurrence of pathogens, information that can clarify risks and aid the prioritization of conservation actions.</p>","language":"English","publisher":"Ecological Society of America","doi":"10.1002/eap.2785","usgsCitation":"Hossack, B., Oja, E.B., Owens, A., Hall, D.L., Cobos, C., Crawford, C.L., Goldberg, C.S., Hedwell, S., Howell, P., Lemos-Espinal, J.A., MacVean, S.K., McCaffery, M., Mosley, C., Muths, E., Sigafus, B., Sredl, M.J., and Rorabaugh, J.C., 2023, Empirical evidence for effects of invasive American Bullfrogs on occurrence of native amphibians and emerging pathogens: Ecological Applications, v. 33, no. 2, e2785, 14 p., https://doi.org/10.1002/eap.2785.","productDescription":"e2785, 14 p.","ipdsId":"IP-138220","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":445149,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/eap.2785","text":"Publisher Index Page"},{"id":411339,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"33","issue":"2","noUsgsAuthors":false,"publicationDate":"2023-01-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Hossack, Blake R. 0000-0001-7456-9564","orcid":"https://orcid.org/0000-0001-7456-9564","contributorId":229347,"corporation":false,"usgs":true,"family":"Hossack","given":"Blake R.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":860842,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Oja, Emily B","contributorId":300578,"corporation":false,"usgs":false,"family":"Oja","given":"Emily","email":"","middleInitial":"B","affiliations":[{"id":36523,"text":"University of Montana","active":true,"usgs":false}],"preferred":false,"id":860843,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Owens, Audrey K","contributorId":288932,"corporation":false,"usgs":false,"family":"Owens","given":"Audrey K","affiliations":[{"id":61907,"text":"AGFD","active":true,"usgs":false}],"preferred":false,"id":860844,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hall, David L.","contributorId":222395,"corporation":false,"usgs":false,"family":"Hall","given":"David","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":860845,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cobos, Cassidi","contributorId":300580,"corporation":false,"usgs":false,"family":"Cobos","given":"Cassidi","email":"","affiliations":[{"id":38107,"text":"Turner Endangered Species Fund","active":true,"usgs":false}],"preferred":false,"id":860846,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Crawford, Catherine L.","contributorId":191976,"corporation":false,"usgs":false,"family":"Crawford","given":"Catherine","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":860847,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Goldberg, Caren S.","contributorId":76879,"corporation":false,"usgs":false,"family":"Goldberg","given":"Caren","email":"","middleInitial":"S.","affiliations":[{"id":5132,"text":"Washington State University, Pullman","active":true,"usgs":false}],"preferred":false,"id":860848,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hedwell, Shaula","contributorId":300583,"corporation":false,"usgs":false,"family":"Hedwell","given":"Shaula","email":"","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":860849,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Howell, Paige E.","contributorId":173495,"corporation":false,"usgs":false,"family":"Howell","given":"Paige E.","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":860850,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Lemos-Espinal, Julio A.","contributorId":237891,"corporation":false,"usgs":false,"family":"Lemos-Espinal","given":"Julio","email":"","middleInitial":"A.","affiliations":[{"id":47636,"text":"FES Iztacala UNAM","active":true,"usgs":false}],"preferred":false,"id":860851,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"MacVean, Susan K","contributorId":300586,"corporation":false,"usgs":false,"family":"MacVean","given":"Susan","email":"","middleInitial":"K","affiliations":[{"id":12922,"text":"Arizona Game and Fish Department","active":true,"usgs":false}],"preferred":false,"id":860852,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"McCaffery, Magnus","contributorId":288936,"corporation":false,"usgs":false,"family":"McCaffery","given":"Magnus","email":"","affiliations":[{"id":38107,"text":"Turner Endangered Species Fund","active":true,"usgs":false}],"preferred":false,"id":860853,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Mosley, Cody","contributorId":300589,"corporation":false,"usgs":false,"family":"Mosley","given":"Cody","email":"","affiliations":[{"id":12922,"text":"Arizona Game and Fish Department","active":true,"usgs":false}],"preferred":false,"id":860854,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Muths, Erin L. 0000-0002-5498-3132","orcid":"https://orcid.org/0000-0002-5498-3132","contributorId":245922,"corporation":false,"usgs":true,"family":"Muths","given":"Erin L.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":860855,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Sigafus, Brent H. 0000-0002-7422-8927","orcid":"https://orcid.org/0000-0002-7422-8927","contributorId":264740,"corporation":false,"usgs":true,"family":"Sigafus","given":"Brent H.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":860856,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Sredl, Micahel J","contributorId":300592,"corporation":false,"usgs":false,"family":"Sredl","given":"Micahel","email":"","middleInitial":"J","affiliations":[{"id":12922,"text":"Arizona Game and Fish Department","active":true,"usgs":false}],"preferred":false,"id":860857,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Rorabaugh, James C.","contributorId":191978,"corporation":false,"usgs":false,"family":"Rorabaugh","given":"James","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":860858,"contributorType":{"id":1,"text":"Authors"},"rank":17}]}}
,{"id":70241549,"text":"70241549 - 2023 - Using landscape genomics to delineate future adaptive potential for climate change in the Yosemite toad (Anaxyrus canorus)","interactions":[],"lastModifiedDate":"2023-03-23T14:23:17.048886","indexId":"70241549","displayToPublicDate":"2022-12-07T09:19:05","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1601,"text":"Evolutionary Applications","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Using landscape genomics to delineate future adaptive potential for climate change in the Yosemite toad (Anaxyrus canorus)","title":"Using landscape genomics to delineate future adaptive potential for climate change in the Yosemite toad (Anaxyrus canorus)","docAbstract":"<p><span>An essential goal in conservation biology is delineating population units that maximize the probability of species persisting into the future and adapting to future environmental change. However, future-facing conservation concerns are often addressed using retrospective patterns that could be irrelevant. We recommend a novel landscape genomics framework for delineating future “Geminate Evolutionary Units” (GEUs) in a focal species: (1) identify loci under environmental selection, (2) model and map adaptive conservation units that may spawn future lineages, (3) forecast relative selection pressures on each future lineage, and (4) estimate their fitness and likelihood of persistence using geo-genomic simulations. Using this process, we delineated conservation units for the Yosemite toad (</span><i>Anaxyrus canorus</i><span>), a U.S. federally threatened species that is highly vulnerable to climate change. We used a genome-wide dataset, redundancy analysis, and Bayesian association methods to identify 24 candidate loci responding to climatic selection (</span><i>R</i><sup>2</sup><span>&nbsp;ranging from 0.09 to 0.52), after controlling for demographic structure. Candidate loci included genes such as MAP3K5, involved in cellular response to environmental change. We then forecasted future genomic response to climate change using the multivariate machine learning algorithm Gradient Forests. Based on all available evidence, we found three GEUs in Yosemite National Park, reflecting contrasting adaptive optima: YF-North (high winter snowpack with moderate summer rainfall), YF-East (low to moderate snowpack with high summer rainfall), and YF-Low-Elevation (low snowpack and rainfall). Simulations under the RCP 8.5 climate change scenario suggest that the species will decline by 29% over 90 years, but the highly diverse YF-East lineage will be least impacted for two reasons: (1) geographically it will be sheltered from the largest climatic selection pressures, and (2) its standing genetic diversity will promote a faster adaptive response. Our approach provides a comprehensive strategy for protecting imperiled non-model species with genomic data alone and has wide applicability to other declining species.</span></p>","language":"English","publisher":"Wiley","doi":"10.1111/eva.13511","usgsCitation":"Maier, P., Vandergast, A.G., and Bohonak, A.J., 2023, Using landscape genomics to delineate future adaptive potential for climate change in the Yosemite toad (Anaxyrus canorus): Evolutionary Applications, v. 16, p. 74-97, https://doi.org/10.1111/eva.13511.","productDescription":"24 p.","startPage":"74","endPage":"97","ipdsId":"IP-147179","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":445156,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/eva.13511","text":"Publisher Index Page"},{"id":414614,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Kings Canyon National Park, Yosemite National Park","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -118.85061210634456,\n              36.52123522076397\n            ],\n            [\n              -118.13910750098108,\n              36.616475004823215\n            ],\n            [\n              -118.44742616330538,\n              37.41654854711554\n            ],\n            [\n              -119.44353261081429,\n              38.35710042889701\n            ],\n            [\n              -120.2024708565354,\n              38.166222753255624\n            ],\n            [\n              -120.45742667345743,\n              37.99820964775573\n            ],\n            [\n              -119.61547955711029,\n              37.360016749403826\n            ],\n            [\n              -118.85061210634456,\n              36.52123522076397\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"16","noUsgsAuthors":false,"publicationDate":"2022-12-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Maier, Paul A. 0000-0003-0851-8827","orcid":"https://orcid.org/0000-0003-0851-8827","contributorId":221033,"corporation":false,"usgs":false,"family":"Maier","given":"Paul A.","affiliations":[{"id":40313,"text":"Department of Biology, San Diego State","active":true,"usgs":false}],"preferred":false,"id":867267,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Vandergast, Amy G. 0000-0002-7835-6571 avandergast@usgs.gov","orcid":"https://orcid.org/0000-0002-7835-6571","contributorId":3963,"corporation":false,"usgs":true,"family":"Vandergast","given":"Amy","email":"avandergast@usgs.gov","middleInitial":"G.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":867268,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bohonak, Andrew J.","contributorId":195156,"corporation":false,"usgs":false,"family":"Bohonak","given":"Andrew","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":867269,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70242068,"text":"70242068 - 2023 - Earth’s upper crust seismically excited by infrasound from the 2022 Hunga Tonga–Hunga Ha’apai eruption, Tonga","interactions":[],"lastModifiedDate":"2023-04-06T12:10:27.3548","indexId":"70242068","displayToPublicDate":"2022-12-07T07:08:40","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"Earth’s upper crust seismically excited by infrasound from the 2022 Hunga Tonga–Hunga Ha’apai eruption, Tonga","docAbstract":"<p>Records of pressure variations on seismographs were historically considered unwanted noise; however, increased deployments of collocated seismic and acoustic instrumentation have driven recent efforts to use this effect induced by both wind and anthropogenic explosions to invert for near‐surface Earth structure. These studies have been limited to shallow structure because the pressure signals have relatively short wavelengths (&lt;∼300&nbsp;m). However, the 2022 eruption of Hunga Tonga–Hunga Ha’apai (also called “Hunga”) volcano in Tonga generated rare, globally observed, high‐amplitude infrasound signals with acoustic wavelengths of tens of kilometers. In this study, we examine the acoustic‐to‐seismic coupling generated by the Hunga eruption across 82 Global Seismographic Network (GSN) stations and show that ground motion amplitudes are related to upper (0 to ∼5&nbsp;km) crust material properties. We find high (&gt;0.8) correlations between pressure and vertical component ground motion at 83% of the stations, but only 30% of stations show this on the radial component, likely due to complex tilt effects. We use average elastic properties in the upper 5.2&nbsp;km from the CRUST1.0 model to estimate vertical seismic/acoustic coupling coefficients (<span class=\"inline-formula no-formula-id\"><span>⁠</span><span id=\"MathJax-Element-1-Frame\" class=\"MathJax\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><msub xmlns=&quot;&quot;><mi>S</mi><mi>V</mi></msub><mo xmlns=&quot;&quot;>/</mo><mi xmlns=&quot;&quot;>A</mi></math>\"><span id=\"MathJax-Span-1\" class=\"math\"><span id=\"MathJax-Span-2\" class=\"mrow\"><span id=\"MathJax-Span-3\" class=\"msub\"></span></span></span></span></span></p>","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220220252","usgsCitation":"Anthony, R.E., Ringler, A.T., Tanimoto, T., Matoza, R., De Angelis, S., and Wilson, D.C., 2023, Earth’s upper crust seismically excited by infrasound from the 2022 Hunga Tonga–Hunga Ha’apai eruption, Tonga: Seismological Research Letters, v. 97, no. 2A, p. 603-616, https://doi.org/10.1785/0220220252.","productDescription":"14 p.","startPage":"603","endPage":"616","ipdsId":"IP-143162","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":415331,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Tonga","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              184.1901765996289,\n              -19.66876668653113\n            ],\n            [\n              184.1901765996289,\n              -22.45584595251242\n            ],\n            [\n              186.38649745518308,\n              -22.45584595251242\n            ],\n            [\n              186.38649745518308,\n              -19.66876668653113\n            ],\n            [\n              184.1901765996289,\n              -19.66876668653113\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"97","issue":"2A","noUsgsAuthors":false,"publicationDate":"2022-12-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Anthony, Robert 0000-0001-7089-8846 reanthony@usgs.gov","orcid":"https://orcid.org/0000-0001-7089-8846","contributorId":202829,"corporation":false,"usgs":true,"family":"Anthony","given":"Robert","email":"reanthony@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":868751,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ringler, Adam T. 0000-0002-9839-4188 aringler@usgs.gov","orcid":"https://orcid.org/0000-0002-9839-4188","contributorId":3946,"corporation":false,"usgs":true,"family":"Ringler","given":"Adam","email":"aringler@usgs.gov","middleInitial":"T.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":868752,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tanimoto, Toshiro","contributorId":303974,"corporation":false,"usgs":false,"family":"Tanimoto","given":"Toshiro","email":"","affiliations":[{"id":36524,"text":"University of California, Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":868753,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Matoza, Robin","contributorId":268788,"corporation":false,"usgs":false,"family":"Matoza","given":"Robin","affiliations":[{"id":7168,"text":"UCSB","active":true,"usgs":false}],"preferred":false,"id":868754,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"De Angelis, Silvio","contributorId":172953,"corporation":false,"usgs":false,"family":"De Angelis","given":"Silvio","affiliations":[{"id":27128,"text":"Univ. of Liverpool","active":true,"usgs":false}],"preferred":false,"id":868755,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wilson, David C. 0000-0003-2582-5159 dwilson@usgs.gov","orcid":"https://orcid.org/0000-0003-2582-5159","contributorId":145580,"corporation":false,"usgs":true,"family":"Wilson","given":"David","email":"dwilson@usgs.gov","middleInitial":"C.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":868756,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70238766,"text":"70238766 - 2023 - Historical Structure from Motion (HSfM): Automated processing of historical aerial photographs for long-term topographic change analysis","interactions":[],"lastModifiedDate":"2022-12-08T12:51:26.352949","indexId":"70238766","displayToPublicDate":"2022-12-07T06:46:28","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3254,"text":"Remote Sensing of Environment","printIssn":"0034-4257","active":true,"publicationSubtype":{"id":10}},"title":"Historical Structure from Motion (HSfM): Automated processing of historical aerial photographs for long-term topographic change analysis","docAbstract":"<p><span>Precisely measuring the Earth’s changing surface on decadal to centennial time scales is critical for many science and engineering applications, yet long-term records of quantitative landscape change are often temporally and geographically sparse. Archives of scanned historical aerial photographs provide an opportunity to augment these records with accurate elevation measurements that capture the historical state of the Earth surface. Structure from Motion (SfM) photogrammetry workflows produce high-quality digital elevation models (DEMs) and orthoimage mosaics from these historical images, but time-intensive tasks like manual image preprocessing (e.g., fiducial marker identification) and ground control point (GCP) selection impede processing at scale. We developed an automated method to process historical images and generate self-consistent time series of high-resolution (0.5–2&nbsp;m) DEMs and orthomosaics, without manual GCP selection. The method relies on SfM to correct camera interior and exterior orientation and a robust multi-stage co-registration approach using modern reference terrain datasets for geolocation refinement. We demonstrate the method using scanned images from the North American Glacier Aerial Photography (NAGAP) archive collected between 1967 and 1997. We present results for two sites with variable photo acquisition geometry and overlap — Mount Baker and South Cascade Glacier in Washington State, USA. The automated method corrects initial camera position errors of several kilometers and produces accurately georeferenced, high-resolution DEMs and orthoimages, regardless of camera configuration, acquisition geometry, terrain characteristics, and reference DEM properties. The average RMS reprojection error following bundle adjustment optimization was 0.67 px (0.15&nbsp;m) for the 261 images contributing to 10 final DEM mosaics between 1970 and 1992 at Mount Baker, and 0.65 px (0.13&nbsp;m) for the 243 images contributing to 18 individual DEMs between 1967 and 1997 at South Cascade Glacier. The relative accuracy of elevation values in the historical time series stacks was 0.68&nbsp;m at Mount Baker and 0.37&nbsp;m at South Cascade Glacier. Our products have reduced systematic error and improved accuracy compared to DEM products generated using SfM with manual GCP selection. Final elevation change measurement precision was&nbsp;</span><span class=\"math\"><span id=\"MathJax-Element-1-Frame\" class=\"MathJax_SVG\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><mo is=&quot;true&quot;>&amp;#x223C;</mo></math>\"><span class=\"MJX_Assistive_MathML\">∼</span></span></span><span>0.7–1.0&nbsp;m over a 30-year period, enabling the study of processes with rates as low as&nbsp;</span><span class=\"math\"><span id=\"MathJax-Element-2-Frame\" class=\"MathJax_SVG\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><mo is=&quot;true&quot;>&amp;#x223C;</mo></math>\"><span class=\"MJX_Assistive_MathML\">∼</span></span></span><span>1-3 cm/yr. Our results demonstrate the potential of this scalable method to rapidly process archives of historical imagery and deliver new quantitative insights on long-term geodetic change and Earth surface processes.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.rse.2022.113379","usgsCitation":"Knuth, F., Shean, D., Bhushan, S., Schwat, E., Alexandrov, O., McNeil, C., Dehecq, A., Florentine, C., and O'Neel, S., 2023, Historical Structure from Motion (HSfM): Automated processing of historical aerial photographs for long-term topographic change analysis: Remote Sensing of Environment, v. 285, 113379, 19 p., https://doi.org/10.1016/j.rse.2022.113379.","productDescription":"113379, 19 p.","ipdsId":"IP-141221","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":445159,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.rse.2022.113379","text":"Publisher Index Page"},{"id":410195,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Mount Baker, South Cascade Glacier","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -122.0207101235892,\n              48.935452732185865\n            ],\n            [\n              -122.0207101235892,\n              48.367766528622326\n            ],\n            [\n              -121.2492481974785,\n              48.367766528622326\n            ],\n            [\n              -121.2492481974785,\n              48.935452732185865\n            ],\n            [\n              -122.0207101235892,\n              48.935452732185865\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"285","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Knuth, Friedrich","contributorId":299741,"corporation":false,"usgs":false,"family":"Knuth","given":"Friedrich","email":"","affiliations":[],"preferred":false,"id":858513,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shean, David","contributorId":299742,"corporation":false,"usgs":false,"family":"Shean","given":"David","affiliations":[],"preferred":false,"id":858514,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bhushan, Shashank","contributorId":299743,"corporation":false,"usgs":false,"family":"Bhushan","given":"Shashank","email":"","affiliations":[],"preferred":false,"id":858515,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schwat, Eli","contributorId":299744,"corporation":false,"usgs":false,"family":"Schwat","given":"Eli","email":"","affiliations":[],"preferred":false,"id":858516,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Alexandrov, Oleg","contributorId":299745,"corporation":false,"usgs":false,"family":"Alexandrov","given":"Oleg","affiliations":[],"preferred":false,"id":858517,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McNeil, Christopher J. 0000-0003-4170-0428 cmcneil@usgs.gov","orcid":"https://orcid.org/0000-0003-4170-0428","contributorId":5803,"corporation":false,"usgs":true,"family":"McNeil","given":"Christopher J.","email":"cmcneil@usgs.gov","affiliations":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":858518,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Dehecq, Amaury","contributorId":299746,"corporation":false,"usgs":false,"family":"Dehecq","given":"Amaury","email":"","affiliations":[],"preferred":false,"id":858519,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Florentine, Caitlyn 0000-0002-7028-0963","orcid":"https://orcid.org/0000-0002-7028-0963","contributorId":205964,"corporation":false,"usgs":true,"family":"Florentine","given":"Caitlyn","email":"","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":858520,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"O'Neel, Shad","contributorId":299747,"corporation":false,"usgs":false,"family":"O'Neel","given":"Shad","affiliations":[],"preferred":false,"id":858521,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70238767,"text":"70238767 - 2023 - Estimating reproductive and juvenile survival rates when offspring ages are uncertain: A novel multievent mark-resight model with beluga whale case study","interactions":[],"lastModifiedDate":"2023-02-14T14:46:31.815152","indexId":"70238767","displayToPublicDate":"2022-12-06T06:33:13","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2717,"text":"Methods in Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Estimating reproductive and juvenile survival rates when offspring ages are uncertain: A novel multievent mark-resight model with beluga whale case study","docAbstract":"<ol class=\"\"><li>Understanding the survival and reproductive rates of a population is critical to determining its long-term dynamics and viability. Mark-resight models are often used to estimate these demographic rates, but estimation of survival and reproductive rates is challenging, especially for wide-ranging, patchily distributed, or cryptic species. In particular, existing mark-resight models cannot accommodate data from populations in which offspring remain with parents for multiple years, are not always detected, and cannot be aged with certainty.</li><li>Here we describe a Bayesian multievent mark-resight modelling framework that uses all available adult and adult-offspring sightings (including sightings with older offspring of uncertain age) to estimate reproductive rates and survival rates of adults and juveniles. We extend existing multievent mark-resight models that typically only incorporate adult breeding state uncertainty by additionally accounting for age uncertainty in unmarked offspring and uncertainty in the duration of the mother-offspring association. We describe our model in general terms and with a simple illustrative example, then apply it in a more complex empirical setting using 13 years of photo-ID data from a critically endangered population of beluga whales<span>&nbsp;</span><i>Delphinapterus leucas</i>. We evaluated model performance using simulated data under a range of sample sizes, and adult and offspring detection rates.</li><li>Applying our model to the beluga data yielded precise estimates for all demographic rates of interest (despite substantial uncertainty in calf ages), including nonbreeder survival and reproductive rates lower than in other beluga populations. Simulations suggested our model yields asymptotically unbiased parameter estimates with good precision and low bias even with moderate sample sizes and detection rates.</li><li>This work represents an important new development in multievent mark-resight modelling, allowing estimation of reproductive and juvenile survival rates for populations with extended adult—offspring associations and uncertain offspring ages (e.g. some marine mammals, elephants, bears, great apes, bats and birds). Our model facilitated estimation of robust demographic rates for an endangered beluga population that were previously inestimable (e.g. nonbreeder and juvenile survival, reproductive rate) and that will yield new insights into this population's continued decline.</li></ol>","language":"English","publisher":"British Ecological Society","doi":"10.1111/2041-210X.14032","usgsCitation":"Himes Boor, G.K., McGuire, T.L., Warlick, A.J., Taylor, R.L., Converse, S.J., McClung, J.R., and Stephens, A.D., 2023, Estimating reproductive and juvenile survival rates when offspring ages are uncertain: A novel multievent mark-resight model with beluga whale case study: Methods in Ecology and Evolution, v. 14, no. 2, p. 631-642, https://doi.org/10.1111/2041-210X.14032.","productDescription":"12 p.","startPage":"631","endPage":"642","ipdsId":"IP-133177","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":445167,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/2041-210x.14032","text":"Publisher Index Page"},{"id":410192,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"14","issue":"2","noUsgsAuthors":false,"publicationDate":"2022-12-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Himes Boor, Gina K","contributorId":299748,"corporation":false,"usgs":false,"family":"Himes Boor","given":"Gina","email":"","middleInitial":"K","affiliations":[{"id":64940,"text":"Montana State University, Ecology Department","active":true,"usgs":false}],"preferred":false,"id":858522,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McGuire, Tamara L","contributorId":299749,"corporation":false,"usgs":false,"family":"McGuire","given":"Tamara","email":"","middleInitial":"L","affiliations":[{"id":64941,"text":"The Cook Inlet Beluga Whale Photo-ID Project","active":true,"usgs":false}],"preferred":false,"id":858523,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Warlick, Amanda J.","contributorId":299750,"corporation":false,"usgs":false,"family":"Warlick","given":"Amanda","email":"","middleInitial":"J.","affiliations":[{"id":13190,"text":"School of Aquatic and Fishery Sciences, University of Washington","active":true,"usgs":false}],"preferred":false,"id":858524,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Taylor, Rebecca L. 0000-0001-8459-7614 rebeccataylor@usgs.gov","orcid":"https://orcid.org/0000-0001-8459-7614","contributorId":5112,"corporation":false,"usgs":true,"family":"Taylor","given":"Rebecca","email":"rebeccataylor@usgs.gov","middleInitial":"L.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":858525,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Converse, Sarah J. 0000-0002-3719-5441 sconverse@usgs.gov","orcid":"https://orcid.org/0000-0002-3719-5441","contributorId":173772,"corporation":false,"usgs":true,"family":"Converse","given":"Sarah","email":"sconverse@usgs.gov","middleInitial":"J.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":858526,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McClung, John R","contributorId":299751,"corporation":false,"usgs":false,"family":"McClung","given":"John","email":"","middleInitial":"R","affiliations":[{"id":64941,"text":"The Cook Inlet Beluga Whale Photo-ID Project","active":true,"usgs":false}],"preferred":false,"id":858527,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Stephens, Amber D","contributorId":299752,"corporation":false,"usgs":false,"family":"Stephens","given":"Amber","email":"","middleInitial":"D","affiliations":[{"id":64941,"text":"The Cook Inlet Beluga Whale Photo-ID Project","active":true,"usgs":false}],"preferred":false,"id":858528,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70254686,"text":"70254686 - 2023 - Landscape characteristics influence projected growth rates of stream-resident juvenile salmon in the face of climate change in the Kenai River watershed, south-central Alaska","interactions":[],"lastModifiedDate":"2024-06-10T15:55:37.485154","indexId":"70254686","displayToPublicDate":"2022-12-05T10:51:43","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3624,"text":"Transactions of the American Fisheries Society","active":true,"publicationSubtype":{"id":10}},"title":"Landscape characteristics influence projected growth rates of stream-resident juvenile salmon in the face of climate change in the Kenai River watershed, south-central Alaska","docAbstract":"<h3 id=\"tafs10397-sec-1001-title\" class=\"article-section__sub-title section1\">Objective</h3><p>Climate change is affecting the distribution and productivity of Pacific salmon throughout their range. At high latitudes, warmer temperatures have been associated with increased freshwater growth of juvenile salmon, but it is not clear how long this trend will continue before further warming leads to reduced growth. To explore the potential influence of climate warming on juvenile Chinook and Coho Salmon summer growth rates in southcentral Alaska, we coupled bioenergetics models with temperature sensitivity models for streams across the Kenai River watershed.</p><h3 id=\"tafs10397-sec-1002-title\" class=\"article-section__sub-title section1\">Methods</h3><p>We measured diet (<i>n</i>&nbsp;= 772 stomachs) and growth (<i>n</i>&nbsp;= 3,791 weight/length values) under current conditions and used published air temperature projections to model growth for the 2030–2039 and 2060–2069 decades.</p><h3 id=\"tafs10397-sec-1003-title\" class=\"article-section__sub-title section1\">Result</h3><p>We estimated direct effects of climate warming on juvenile growth (body mass at the end of May–September study period) will be primarily negative, ranging from +5.1% to −22.8% relative to a 2010–2019 baseline. Estimated effects depended on age cohort, feeding rate, and climate scenario. However, an extended growing season from warming could mitigate or offset predicted reductions in growth during midsummer.</p><h3 id=\"tafs10397-sec-1004-title\" class=\"article-section__sub-title section1\">Conclusion</h3><p>Our results illustrate how diverse habitats are expected to produce variation in the magnitude of climate effects throughout juvenile salmon rearing environments.</p>","language":"English","publisher":"American Fisheries Society","doi":"10.1002/tafs.10397","usgsCitation":"Meyer, B.E., Wipfli, M.S., Schoen, E.R., Rinella, D.J., and Falke, J.A., 2023, Landscape characteristics influence projected growth rates of stream-resident juvenile salmon in the face of climate change in the Kenai River watershed, south-central Alaska: Transactions of the American Fisheries Society, v. 152, no. 2, p. 169-186, https://doi.org/10.1002/tafs.10397.","productDescription":"18 p.","startPage":"169","endPage":"186","ipdsId":"IP-118861","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":429770,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Kenai River watershed","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -151.4549403294923,\n              60.880272178096675\n            ],\n            [\n              -151.4549403294923,\n              59.98297350123735\n            ],\n            [\n              -148.89064752578966,\n              59.98297350123735\n            ],\n            [\n              -148.89064752578966,\n              60.880272178096675\n            ],\n            [\n              -151.4549403294923,\n              60.880272178096675\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"152","issue":"2","noUsgsAuthors":false,"publicationDate":"2022-12-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Meyer, B. E.","contributorId":337257,"corporation":false,"usgs":false,"family":"Meyer","given":"B.","email":"","middleInitial":"E.","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":902284,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wipfli, M. S.","contributorId":337258,"corporation":false,"usgs":false,"family":"Wipfli","given":"M.","email":"","middleInitial":"S.","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":902285,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schoen, E. R.","contributorId":337259,"corporation":false,"usgs":false,"family":"Schoen","given":"E.","email":"","middleInitial":"R.","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":902286,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rinella, D. J.","contributorId":337260,"corporation":false,"usgs":false,"family":"Rinella","given":"D.","email":"","middleInitial":"J.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":902287,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Falke, Jeffrey A. 0000-0002-6670-8250 jfalke@usgs.gov","orcid":"https://orcid.org/0000-0002-6670-8250","contributorId":5195,"corporation":false,"usgs":true,"family":"Falke","given":"Jeffrey","email":"jfalke@usgs.gov","middleInitial":"A.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":902288,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70239272,"text":"70239272 - 2023 - Future direction of fuels management in sagebrush rangelands","interactions":[],"lastModifiedDate":"2023-01-06T14:39:39.210498","indexId":"70239272","displayToPublicDate":"2022-12-05T08:39:08","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3228,"text":"Rangeland Ecology and Management","onlineIssn":"1551-5028","printIssn":"1550-7424","active":true,"publicationSubtype":{"id":10}},"title":"Future direction of fuels management in sagebrush rangelands","docAbstract":"<p><span>Sagebrush ecosystems in the United States have been declining since EuroAmerican settlement, largely due to agricultural and urban development, invasive species, and altered fire regimes, resulting in loss of biodiversity and wildlife habitat. To combat continued conversion to undesirable ecological states and loss of habitat to invasive species fueled by frequent fire, a variety of fuel treatments, including networks of fuel breaks, are being implemented or proposed in sagebrush ecosystems, particularly in and around the Great Basin. In this forum paper we briefly review current knowledge of common fuel treatment approaches, their intended benefits, potential risks, and limitations. We additionally discuss challenges for fuel treatment strategies in the context of changes in climate, invasive species, wildlife habitat, and human population, and we explore how advances in geospatial technologies, monitoring, and fire behavior modeling, as well as accounting for social context, can improve the efficacy of fuels management in sagebrush ecosystems. Finally, given continued potential for ecosystem transformation, we describe approaches to future fuels management by considering the applicability of the Resist-Accept-Direct (RAD) framework. The intent of the paper is to provide scientists and land managers with key information and a forward-thinking framework for fuels science and adaptive management that can respond to both expected and unexpected changes in sagebrush rangelands.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.rama.2022.10.009","usgsCitation":"Shinneman, D.J., Strand, E., Pellant, M., Abatzoglou, J.T., Brunson, M.W., Glenn, N., Heinrichs, J., Sadegh, M., and Vaillant, N., 2023, Future direction of fuels management in sagebrush rangelands: Rangeland Ecology and Management, v. 86, p. 50-63, https://doi.org/10.1016/j.rama.2022.10.009.","productDescription":"14 p.","startPage":"50","endPage":"63","ipdsId":"IP-136593","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":498253,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://scholarworks.boisestate.edu/geo_facpubs/704","text":"External Repository"},{"id":411487,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"86","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Shinneman, Douglas J. 0000-0002-4909-5181 dshinneman@usgs.gov","orcid":"https://orcid.org/0000-0002-4909-5181","contributorId":147745,"corporation":false,"usgs":true,"family":"Shinneman","given":"Douglas","email":"dshinneman@usgs.gov","middleInitial":"J.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":860966,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Strand, Eva","contributorId":82611,"corporation":false,"usgs":false,"family":"Strand","given":"Eva","affiliations":[{"id":6711,"text":"University of Idaho, Moscow ID","active":true,"usgs":false}],"preferred":false,"id":860967,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pellant, Mike","contributorId":178257,"corporation":false,"usgs":false,"family":"Pellant","given":"Mike","email":"","affiliations":[],"preferred":false,"id":860968,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Abatzoglou, John T.","contributorId":191729,"corporation":false,"usgs":false,"family":"Abatzoglou","given":"John","email":"","middleInitial":"T.","affiliations":[{"id":33345,"text":" University of Idaho","active":true,"usgs":false}],"preferred":false,"id":860969,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Brunson, Mark W.","contributorId":195697,"corporation":false,"usgs":false,"family":"Brunson","given":"Mark","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":860970,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Glenn, Nancy","contributorId":181558,"corporation":false,"usgs":false,"family":"Glenn","given":"Nancy","affiliations":[],"preferred":false,"id":860971,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Heinrichs, Julie A. 0000-0001-7733-5034","orcid":"https://orcid.org/0000-0001-7733-5034","contributorId":240888,"corporation":false,"usgs":false,"family":"Heinrichs","given":"Julie A.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":860972,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Sadegh, Mojtaba","contributorId":298279,"corporation":false,"usgs":false,"family":"Sadegh","given":"Mojtaba","affiliations":[{"id":16201,"text":"Boise State University","active":true,"usgs":false}],"preferred":false,"id":860973,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Vaillant, Nicole","contributorId":140987,"corporation":false,"usgs":false,"family":"Vaillant","given":"Nicole","affiliations":[{"id":13638,"text":"Western Wildland environmental threat assessment Center","active":true,"usgs":false}],"preferred":false,"id":860974,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70238758,"text":"70238758 - 2023 - Modeling the dynamic penetration depth of post-1950s water in unconfined aquifers using environmental tracers: Central Valley, California","interactions":[],"lastModifiedDate":"2022-12-07T13:11:33.679909","indexId":"70238758","displayToPublicDate":"2022-12-05T07:09:26","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Modeling the dynamic penetration depth of post-1950s water in unconfined aquifers using environmental tracers: Central Valley, California","docAbstract":"<div id=\"abstracts\" class=\"Abstracts u-font-serif\"><div id=\"ab010\" class=\"abstract author\"><div id=\"as010\"><p id=\"sp0010\">The penetration depth of post-1950s recharge (D-1950) in aquifers is a marker that is frequently used to identify groundwater that is susceptible to anthropogenic contamination. Here, we compute D-1950 values at wells, interpolate them in space, and project them across time to map the moving front of modern recharge in four dimensions in the Central Valley aquifer system, California, USA. Tracers of groundwater age (tritium, carbon-14, noble gases, sulfur hexafluoride, and chlorofluorocarbons) were collected at 650 wells spatially distributed throughout the Central Valley and were fit to a lumped-parameter model that assumes a logarithmic age-depth profile in the aquifer. For samples where tritium was present (&gt;0.3 tritium units), the model was used to predict D-1950 at wells screened above or across the modern-premodern interface (n&nbsp;=&nbsp;484). Wells with samples where tritium was absent (≤0.3 tritium units) were used to define the depth beyond which groundwater is completely premodern (n&nbsp;=&nbsp;166). Predicted D-1950 values were below the depth of screen bottoms for wells where groundwater is completely modern, and above the depth of screen tops for wells where groundwater is completely premodern. The interpolated surface of D-1950 is dynamic, less prone to extreme values, and produces maps with lower interpolation errors due to a higher spatial density of wells than maps based on the depth of premodern groundwater. Between 2005 and 2025, D-1950 is expected to deepen by 11 and 12&nbsp;m in the northern and southern parts of the Central Valley, respectively. Areas where D-1950 increases rapidly are likely to see increases in nitrate and other anthropogenic contaminants associated with the downward moving front of modern water.</p></div></div></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2022.128818","usgsCitation":"Faulkner, K., Jurgens, B., Voss, S., Dupuy, D., and Levy, Z., 2023, Modeling the dynamic penetration depth of post-1950s water in unconfined aquifers using environmental tracers: Central Valley, California: Journal of Hydrology, v. 616, 128818, 14 p., https://doi.org/10.1016/j.jhydrol.2022.128818.","productDescription":"128818, 14 p.","ipdsId":"IP-130865","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":435552,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9MA4MBP","text":"USGS data release","linkHelpText":"Central Valley Aquifer Age Dating Web Tool"},{"id":435551,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9CL07RX","text":"USGS data release","linkHelpText":"Data for assessing the penetration depth post-1950s water in the Central Valley aquifer system, California (July 2022)"},{"id":410157,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Central Valley","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -121.8909609860649,\n              40.725785462097406\n            ],\n            [\n              -123.12090740207057,\n              41.057846544130285\n            ],\n            [\n              -122.81342079806942,\n              39.65201564752738\n            ],\n            [\n              -122.02274095920826,\n              37.69748533018377\n            ],\n            [\n              -120.74886788548812,\n              35.654353146053566\n            ],\n            [\n              -118.72824163062074,\n              34.54025513434168\n            ],\n            [\n              -117.67400184547287,\n              35.43991112996163\n            ],\n            [\n              -120.35352796605754,\n              38.389359440096\n            ],\n            [\n              -121.8909609860649,\n              40.725785462097406\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"616","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Faulkner, Kirsten 0000-0003-1628-2877","orcid":"https://orcid.org/0000-0003-1628-2877","contributorId":222341,"corporation":false,"usgs":true,"family":"Faulkner","given":"Kirsten","email":"","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":858488,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jurgens, Bryant 0000-0002-1572-113X","orcid":"https://orcid.org/0000-0002-1572-113X","contributorId":203430,"corporation":false,"usgs":true,"family":"Jurgens","given":"Bryant","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":858489,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Voss, Stefan 0000-0003-1214-9358","orcid":"https://orcid.org/0000-0003-1214-9358","contributorId":217888,"corporation":false,"usgs":true,"family":"Voss","given":"Stefan","email":"","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":858490,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dupuy, Danielle 0000-0001-9007-641X","orcid":"https://orcid.org/0000-0001-9007-641X","contributorId":222277,"corporation":false,"usgs":true,"family":"Dupuy","given":"Danielle","email":"","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":858491,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Levy, Zeno F. 0000-0003-4580-2309","orcid":"https://orcid.org/0000-0003-4580-2309","contributorId":222340,"corporation":false,"usgs":true,"family":"Levy","given":"Zeno","middleInitial":"F.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":858492,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70238826,"text":"70238826 - 2023 - Learning from arid and urban aquatic ecosystems to inform more sustainable and resilient futures","interactions":[],"lastModifiedDate":"2022-12-13T12:52:49.994084","indexId":"70238826","displayToPublicDate":"2022-12-02T06:50:49","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Learning from arid and urban aquatic ecosystems to inform more sustainable and resilient futures","docAbstract":"<div id=\"ab015\" class=\"abstract author\"><div id=\"as015\"><p id=\"sp0015\">The hydrology and aquatic ecology of arid environments has long been understudied relative to temperate regions. Yet spatially and temporally intermittent and ephemeral waters characterized by flashy hydrographs typify arid regions that comprise a substantial proportion of the Earth. Additionally, drought, intense storms, and human modification of landscapes increasingly affect many temperate regions, resulting in hydrologic regimes more similar to aridlands. Here we review the contributions of Dr. Nancy Grimm to aridland hydrology and ecology, and applications of these insights to urban ecosystems and resilience of social-ecological-technological systems. Grimm catalyzed study of nitrogen cycling in streams and characterized feedbacks between surface water-groundwater exchange, nitrogen transformations, and aquatic biota. In aridlands, outcomes of these interactions depend on short- and long-term variation in the hydrologic regime. Grimm and colleagues applied hydrological and biogeochemical insights gained from study of aridland streams to urban ecosystems, integrating engineering, social and behavioral sciences, and geography. These studies evolved from characterizing the spatial heterogeneity of urban systems (i.e., watersheds, novel aquatic systems) and its influence on nutrient dynamics to an approach that evaluated human decision-making as a driver of disturbance regimes and changes in ecosystem function. Finally, Grimm and colleagues have applied principles of urban ecology to look toward the future of cities, considering scenarios of sustainable and resilient futures. We identify cross-cutting themes and approaches that have motivated discoveries across Grimm’s multi-decadal career, including spatial and temporal heterogeneity, hydrologic connectivity and regime, disturbance, systems thinking, and resilience. Finally, we emphasize Grimm’s broad contributions to science via support of long-term research, dedication to mentoring, and extensive collaborations that facilitated transdisciplinary research.</p></div></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2022.128841","usgsCitation":"McPhillips, L., Berbes-Blazquez, M., Hale, R., Harms, T., Bisht, V., Caughman, L., Clinton, S., Cook, E., Dong, X., Edmonds, J., Gergel, S., Gomez, R., Hopkins, K.G., Iwaniec, D., Kim, Y., Kuhn, A., Larson, L., Lewis, D., Marti, E., Palta, M.M., Roach, W.J., and Ye, L., 2023, Learning from arid and urban aquatic ecosystems to inform more sustainable and resilient futures: Journal of Hydrology, v. 616, 128841, 13 p., https://doi.org/10.1016/j.jhydrol.2022.128841.","productDescription":"128841, 13 p.","ipdsId":"IP-145383","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":445177,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jhydrol.2022.128841","text":"Publisher Index Page"},{"id":410355,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"616","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"McPhillips, Lauren","contributorId":270777,"corporation":false,"usgs":false,"family":"McPhillips","given":"Lauren","affiliations":[{"id":36985,"text":"Penn State University","active":true,"usgs":false}],"preferred":false,"id":858804,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Berbes-Blazquez, Marta","contributorId":299828,"corporation":false,"usgs":false,"family":"Berbes-Blazquez","given":"Marta","email":"","affiliations":[{"id":6655,"text":"University of Waterloo","active":true,"usgs":false}],"preferred":false,"id":858805,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hale, Rebecca 0000-0002-3552-3691","orcid":"https://orcid.org/0000-0002-3552-3691","contributorId":195753,"corporation":false,"usgs":false,"family":"Hale","given":"Rebecca","email":"","affiliations":[{"id":12865,"text":"Smithsonian Institute","active":true,"usgs":false}],"preferred":false,"id":858806,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Harms, Tamara K","contributorId":217764,"corporation":false,"usgs":false,"family":"Harms","given":"Tamara K","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":858807,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bisht, Vanya","contributorId":299829,"corporation":false,"usgs":false,"family":"Bisht","given":"Vanya","email":"","affiliations":[{"id":6607,"text":"Arizona State University","active":true,"usgs":false}],"preferred":false,"id":858808,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Caughman, Lilana","contributorId":299830,"corporation":false,"usgs":false,"family":"Caughman","given":"Lilana","email":"","affiliations":[{"id":6607,"text":"Arizona State University","active":true,"usgs":false}],"preferred":false,"id":858809,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Clinton, Sandra","contributorId":299831,"corporation":false,"usgs":false,"family":"Clinton","given":"Sandra","email":"","affiliations":[{"id":36866,"text":"University of North Carolina Charlotte","active":true,"usgs":false}],"preferred":false,"id":858810,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Cook, Elizabeth","contributorId":299832,"corporation":false,"usgs":false,"family":"Cook","given":"Elizabeth","email":"","affiliations":[{"id":64959,"text":"Barnard College-Columbia University","active":true,"usgs":false}],"preferred":false,"id":858811,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Dong, Xiaoli","contributorId":299833,"corporation":false,"usgs":false,"family":"Dong","given":"Xiaoli","email":"","affiliations":[{"id":7214,"text":"University of California, Davis","active":true,"usgs":false}],"preferred":false,"id":858812,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Edmonds, Jennifer","contributorId":299834,"corporation":false,"usgs":false,"family":"Edmonds","given":"Jennifer","email":"","affiliations":[{"id":24777,"text":"Nevada State College","active":true,"usgs":false}],"preferred":false,"id":858813,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Gergel, Sarah","contributorId":299835,"corporation":false,"usgs":false,"family":"Gergel","given":"Sarah","email":"","affiliations":[{"id":36972,"text":"University of British Columbia","active":true,"usgs":false}],"preferred":false,"id":858814,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Gomez, Rosa","contributorId":299836,"corporation":false,"usgs":false,"family":"Gomez","given":"Rosa","email":"","affiliations":[{"id":47555,"text":"University of Murcia","active":true,"usgs":false}],"preferred":false,"id":858815,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Hopkins, Kristina G. 0000-0003-1699-9384 khopkins@usgs.gov","orcid":"https://orcid.org/0000-0003-1699-9384","contributorId":195604,"corporation":false,"usgs":true,"family":"Hopkins","given":"Kristina","email":"khopkins@usgs.gov","middleInitial":"G.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":858816,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Iwaniec, David","contributorId":299837,"corporation":false,"usgs":false,"family":"Iwaniec","given":"David","email":"","affiliations":[{"id":52554,"text":"Georgia State University","active":true,"usgs":false}],"preferred":false,"id":858817,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Kim, Yeowon","contributorId":299838,"corporation":false,"usgs":false,"family":"Kim","given":"Yeowon","email":"","affiliations":[{"id":17786,"text":"Carleton University","active":true,"usgs":false}],"preferred":false,"id":858818,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Kuhn, Amanda","contributorId":299839,"corporation":false,"usgs":false,"family":"Kuhn","given":"Amanda","email":"","affiliations":[{"id":6607,"text":"Arizona State University","active":true,"usgs":false}],"preferred":false,"id":858819,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Larson, Libby","contributorId":299840,"corporation":false,"usgs":false,"family":"Larson","given":"Libby","email":"","affiliations":[{"id":64960,"text":"NASA Goddard Space Flight Center/SSAI","active":true,"usgs":false}],"preferred":false,"id":858820,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Lewis, David Bruce","contributorId":156433,"corporation":false,"usgs":false,"family":"Lewis","given":"David Bruce","affiliations":[{"id":7163,"text":"University of South Florida","active":true,"usgs":false}],"preferred":false,"id":858821,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Marti, Eugenia","contributorId":299842,"corporation":false,"usgs":false,"family":"Marti","given":"Eugenia","email":"","affiliations":[{"id":64961,"text":"Centre d’Estudis Avançats de Blanes","active":true,"usgs":false}],"preferred":false,"id":858822,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Palta, Monica M.","contributorId":221680,"corporation":false,"usgs":false,"family":"Palta","given":"Monica","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":858823,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Roach, W. John","contributorId":299845,"corporation":false,"usgs":false,"family":"Roach","given":"W.","email":"","middleInitial":"John","affiliations":[{"id":64962,"text":"SimBio","active":true,"usgs":false}],"preferred":false,"id":858824,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Ye, Lin","contributorId":299848,"corporation":false,"usgs":false,"family":"Ye","given":"Lin","affiliations":[{"id":32415,"text":"Chinese Academy of Sciences","active":true,"usgs":false}],"preferred":false,"id":858825,"contributorType":{"id":1,"text":"Authors"},"rank":22}]}}
,{"id":70238973,"text":"70238973 - 2023 - Assessment of resource potential from mine tailings using geostatistical modeling for compositions: A methodology and application to Katherine Mine site, Arizona, USA","interactions":[],"lastModifiedDate":"2022-12-20T12:49:04.741255","indexId":"70238973","displayToPublicDate":"2022-12-02T06:37:23","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2302,"text":"Journal of Geochemical Exploration","active":true,"publicationSubtype":{"id":10}},"title":"Assessment of resource potential from mine tailings using geostatistical modeling for compositions: A methodology and application to Katherine Mine site, Arizona, USA","docAbstract":"<p id=\"sp0135\">The mining industry, in most cases, targets a specific valuable commodity that is present in small quantities within large volumes of extracted material. After milling and processing, most of the extracted material and the effluents are stored as waste (tailings) in impoundments, such as dams or waste dumps, or are backfilled into underground mines. In time, tailing materials may become an issue of environmental and health concern due to the hazardous elements, ions, and oxides contained within the waste material. In addition, handling and storage of such waste in dams may pose the risk of dam failure with catastrophic consequences to nature and nearby communities. On the other hand, tailings may offer potential as secondary sources of critical elements (CEs), including rare earth elements (REEs), which may have been overlooked during primary production and processing. Therefore, treating mine tailings as a resource has economic and environmental benefits by reducing the waste from new and historical mine sites through remining. One of the critical steps for taking advantage of these benefits is to spatially quantify the resources and the pollutants, which require the application of adequate data analysis and modeling methods, often to compositional geochemical data. Utilizing adequate methods is especially important for correctly quantifying resource potential, as the quantities will often be at low concentrations.</p><p id=\"sp0140\">This work presents quantification of resource potential (Au, Ag, Cu, Zn, Pb) and elements of environmental concern (Hg and As) from the tailings of a historic mine site, Katherine Mine, AZ, USA. Data reported by the U.S. Bureau of Mines (USBM) after extensive field campaigns in the 1990s, including sampling from tailing impoundment and surrounding areas for geochemical characterization and geophysical surveys, were used. First, compositional data (CoDa) analysis was employed to explore associations of sampling locations, geochemical parts, and the clustering of samples. Next, sequential Gaussian simulation (SGSIM) was applied to samples that showed a genetic link to tailing material after isometric log-ratio transformation (ilr) and mix/max autocorrelation factor (MAF) transformation for spatial modeling and uncertainty evaluation. Geostatistical results revealed spatial variability of concentrations within the tailing area. Uncertainty evaluation based on realizations indicated that Cu (14.27–20.01&nbsp;t), Zn (44.23–76.23&nbsp;t), and Pb (22.56–38.28&nbsp;t) are the most abundant elements within a 5&nbsp;%–95&nbsp;% interval, followed by Ag and Au (~5.3 and 0.18&nbsp;t, at 50th percentile), respectively. Of the elements of health concern, As was found to be ~4.8&nbsp;t (50th percentile) in the tailing area. The work also showed that ~0.51&nbsp;t As, 0.005&nbsp;t Hg, 0.020&nbsp;t of Au, and 0.62&nbsp;t of Ag were carried to Lake Mohave by an ephemeral stream called Katherine Wash, which transects the tailings.</p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.gexplo.2022.107142","usgsCitation":"Karacan, C.O., Erten, O., and Martin-Fernandez, J.A., 2023, Assessment of resource potential from mine tailings using geostatistical modeling for compositions: A methodology and application to Katherine Mine site, Arizona, USA: Journal of Geochemical Exploration, v. 245, 107142, 23 p., https://doi.org/10.1016/j.gexplo.2022.107142.","productDescription":"107142, 23 p.","ipdsId":"IP-142163","costCenters":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":410781,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Katherine Mine site","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -114.66102965470434,\n              35.592576061702815\n            ],\n            [\n              -114.66102965470434,\n              35.179363749635115\n            ],\n            [\n              -114.1226599998257,\n              35.179363749635115\n            ],\n            [\n              -114.1226599998257,\n              35.592576061702815\n            ],\n            [\n              -114.66102965470434,\n              35.592576061702815\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"245","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Karacan, C. Ozgen 0000-0002-0947-8241","orcid":"https://orcid.org/0000-0002-0947-8241","contributorId":201991,"corporation":false,"usgs":true,"family":"Karacan","given":"C.","email":"","middleInitial":"Ozgen","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":859489,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Erten, Oktay","contributorId":300145,"corporation":false,"usgs":false,"family":"Erten","given":"Oktay","email":"","affiliations":[],"preferred":false,"id":859490,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Martin-Fernandez, Josep Antoni","contributorId":300146,"corporation":false,"usgs":false,"family":"Martin-Fernandez","given":"Josep","email":"","middleInitial":"Antoni","affiliations":[],"preferred":false,"id":859491,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70239116,"text":"70239116 - 2023 - Porosity, strength, and alteration – Towards a new volcano stability assessment tool using VNIR-SWIR reflectance spectroscopy","interactions":[],"lastModifiedDate":"2022-12-28T13:48:14.915737","indexId":"70239116","displayToPublicDate":"2022-11-30T07:43:49","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1427,"text":"Earth and Planetary Science Letters","active":true,"publicationSubtype":{"id":10}},"title":"Porosity, strength, and alteration – Towards a new volcano stability assessment tool using VNIR-SWIR reflectance spectroscopy","docAbstract":"<div id=\"ab0010\" class=\"abstract author\"><div id=\"as0010\"><p id=\"sp0090\">Volcano slope stability analysis is a critical component of volcanic hazard assessments and monitoring. However, traditional methods for assessing rock strength require physical samples of rock which may be difficult to obtain or characterize in bulk. Here, visible to shortwave infrared (350–2500 nm; VNIR–SWIR) reflected light spectroscopy on laboratory-tested rock samples from Ruapehu, Ohakuri, Whakaari, and Banks Peninsula (New Zealand), Merapi (Indonesia), Chaos Crags (USA), Styrian Basin (Austria) and La Soufrière de Guadeloupe (Eastern Caribbean) volcanoes was used to design a novel rapid chemometric-based method to estimate uniaxial compressive strength (UCS) and porosity. Our Partial Least Squares Regression models return moderate accuracies for both UCS and porosity, with R<sup>2</sup><span>&nbsp;</span>of 0.43–0.49 and Mean Absolute Percentage Error (MAPE) of 0.2–0.4. When laboratory-measured porosity is included with spectral data, UCS prediction reaches an R<sup>2</sup><span>&nbsp;</span>of 0.82 and MAPE of 0.11. Our models highlight that the observed changes in the UCS are coupled with subtle mineralogical changes due to hydrothermal alteration at wavelengths of 360–438, 532–597, 1405–1455, 2179–2272, 2332–2386, and 2460–2490 nm. These mineralogical changes include mineral replacement, precipitation hydrothermal alteration processes which impact the strength of volcanic rocks, such as mineral replacement, precipitation, and/or silicification. Our approach highlights that spectroscopy can provide a first order assessment of rock strength and/or porosity or be used to complement laboratory porosity-based predictive models. VNIR-SWIR spectroscopy therefore provides an accurate non-destructive way of assessing rock strength and alteration mineralogy, even from remote sensing platforms.</p></div></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.epsl.2022.117929","usgsCitation":"Kereszturi, G., Heap, M.J., Schaefer, L.N., Darmawan, H., Deegan, F.M., Kennedy, B.M., Komorowski, J., Mead, S., Rosas-Carbajal, M., Ryan, A., Troll, V.R., Villeneuve, M.C., and Walter, T., 2023, Porosity, strength, and alteration – Towards a new volcano stability assessment tool using VNIR-SWIR reflectance spectroscopy: Earth and Planetary Science Letters, v. 602, 117929, 12 p., https://doi.org/10.1016/j.epsl.2022.117929.","productDescription":"117929, 12 p.","ipdsId":"IP-144625","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":445187,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.epsl.2022.117929","text":"Publisher Index Page"},{"id":411116,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"602","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Kereszturi, Gabor 0000-0003-4336-2012","orcid":"https://orcid.org/0000-0003-4336-2012","contributorId":247601,"corporation":false,"usgs":false,"family":"Kereszturi","given":"Gabor","email":"","affiliations":[{"id":49587,"text":"Volcanic Risk Solutions, Massey University, Palmerston North, 4474, New Zealand","active":true,"usgs":false}],"preferred":false,"id":860100,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Heap, Michael J. 0000-0002-4748-735X","orcid":"https://orcid.org/0000-0002-4748-735X","contributorId":297882,"corporation":false,"usgs":false,"family":"Heap","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":64429,"text":"Université de Strasbourg","active":true,"usgs":false}],"preferred":false,"id":860101,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schaefer, Lauren N. 0000-0003-3216-7983","orcid":"https://orcid.org/0000-0003-3216-7983","contributorId":241997,"corporation":false,"usgs":true,"family":"Schaefer","given":"Lauren","email":"","middleInitial":"N.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":860102,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Darmawan, Herlan","contributorId":300363,"corporation":false,"usgs":false,"family":"Darmawan","given":"Herlan","email":"","affiliations":[{"id":65091,"text":"Universitas Gadjah Mada","active":true,"usgs":false}],"preferred":false,"id":860103,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Deegan, Frances M. 0000-0002-9065-9225","orcid":"https://orcid.org/0000-0002-9065-9225","contributorId":300364,"corporation":false,"usgs":false,"family":"Deegan","given":"Frances","email":"","middleInitial":"M.","affiliations":[{"id":37671,"text":"Uppsala University","active":true,"usgs":false}],"preferred":false,"id":860104,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kennedy, Ben M. 0000-0001-7235-6493","orcid":"https://orcid.org/0000-0001-7235-6493","contributorId":270276,"corporation":false,"usgs":false,"family":"Kennedy","given":"Ben","email":"","middleInitial":"M.","affiliations":[{"id":37172,"text":"University of Canterbury","active":true,"usgs":false}],"preferred":false,"id":860105,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Komorowski, Jean-Christophe","contributorId":300365,"corporation":false,"usgs":false,"family":"Komorowski","given":"Jean-Christophe","affiliations":[{"id":65092,"text":"Université de Paris","active":true,"usgs":false}],"preferred":false,"id":860106,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Mead, Stuart","contributorId":300366,"corporation":false,"usgs":false,"family":"Mead","given":"Stuart","affiliations":[{"id":13571,"text":"Massey University","active":true,"usgs":false}],"preferred":false,"id":860107,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Rosas-Carbajal, Marina 0000-0002-5393-0389","orcid":"https://orcid.org/0000-0002-5393-0389","contributorId":300367,"corporation":false,"usgs":false,"family":"Rosas-Carbajal","given":"Marina","email":"","affiliations":[{"id":65092,"text":"Université de Paris","active":true,"usgs":false}],"preferred":false,"id":860108,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Ryan, Amy","contributorId":300368,"corporation":false,"usgs":false,"family":"Ryan","given":"Amy","email":"","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":860109,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Troll, Valentin R.","contributorId":300369,"corporation":false,"usgs":false,"family":"Troll","given":"Valentin","email":"","middleInitial":"R.","affiliations":[{"id":37671,"text":"Uppsala University","active":true,"usgs":false}],"preferred":false,"id":860110,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Villeneuve, Marlene C. 0000-0001-6001-0786","orcid":"https://orcid.org/0000-0001-6001-0786","contributorId":300370,"corporation":false,"usgs":false,"family":"Villeneuve","given":"Marlene","email":"","middleInitial":"C.","affiliations":[{"id":65093,"text":"Montanuniversität Leoben","active":true,"usgs":false}],"preferred":false,"id":860111,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Walter, Thomas R.","contributorId":300371,"corporation":false,"usgs":false,"family":"Walter","given":"Thomas R.","affiliations":[{"id":39797,"text":"GFZ German Research Centre for Geosciences","active":true,"usgs":false}],"preferred":false,"id":860112,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}}
,{"id":70240107,"text":"70240107 - 2023 - Impeding access to tributary spawning habitat and releasing experimental fall-timed floods increases brown trout immigration into a dam's tailwater","interactions":[],"lastModifiedDate":"2023-03-01T17:18:46.29359","indexId":"70240107","displayToPublicDate":"2022-11-30T06:36:09","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1169,"text":"Canadian Journal of Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Impeding access to tributary spawning habitat and releasing experimental fall-timed floods increases brown trout immigration into a dam's tailwater","docAbstract":"<div id=\"abstracts\" data-extent=\"frontmatter\"><div class=\"core-container\"><div>River ecosystems have been altered by flow regulation and species introductions. Regulated flow regimes often include releases designed to benefit certain species or restore ecosystem processes, and invasive species suppression programs may include efforts to restrict access to spawning habitat. The impacts of these management interventions are often uncertain. Here, we assess hypotheses regarding introduced brown trout (Salmo trutta) movement in a regulated river. We model mark-recapture data in a multistate framework to assess whether movement was affected by the operation of a tributary weir (restricting access to spawning habitat), experimental releases of fall-timed High Flow Experiments (Fall HFEs), or simply increased during the fall, spawning season. Our results suggest that the presence of the weir led to reduced tributary homing and the release of Fall HFEs stimulated upstream movement and straying. Both effects are of a similar magnitude, however the fall HFE effect is more certain. Our results suggest the expansion of an invasive species was stimulated by management interventions, and demonstrate the potential for unanticipated outcomes of restoration in highly altered river ecosystems.</div></div></div>","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjfas-2022-0231","usgsCitation":"Healy, B.D., Yackulic, C., and Schelly, R.C., 2023, Impeding access to tributary spawning habitat and releasing experimental fall-timed floods increases brown trout immigration into a dam's tailwater: Canadian Journal of Fisheries and Aquatic Sciences, v. 80, no. 3, p. 614-627, https://doi.org/10.1139/cjfas-2022-0231.","productDescription":"14 p.","startPage":"614","endPage":"627","ipdsId":"IP-145826","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":445192,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1139/cjfas-2022-0231","text":"Publisher Index Page"},{"id":412397,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, Utah","otherGeospatial":"Bright Angel Creek, Colorado River, Glen Canyon Dam tailwater, Grand Canyon National Park, Lake Powell,","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -111.5,\n              37.1\n            ],\n            [\n              -114,\n              37.1\n            ],\n            [\n              -114,\n              35.5\n            ],\n            [\n              -111.5,\n              35.5\n            ],\n            [\n              -111.5,\n              37.1\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"80","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Healy, Brian D. 0000-0002-4402-638X","orcid":"https://orcid.org/0000-0002-4402-638X","contributorId":301150,"corporation":false,"usgs":false,"family":"Healy","given":"Brian","email":"","middleInitial":"D.","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":862601,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yackulic, Charles B. 0000-0001-9661-0724","orcid":"https://orcid.org/0000-0001-9661-0724","contributorId":218825,"corporation":false,"usgs":true,"family":"Yackulic","given":"Charles","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":862602,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schelly, Robert C.","contributorId":301154,"corporation":false,"usgs":false,"family":"Schelly","given":"Robert","email":"","middleInitial":"C.","affiliations":[{"id":65320,"text":"Native Fish Ecology and Conservation Program","active":true,"usgs":false}],"preferred":false,"id":862603,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70238685,"text":"70238685 - 2023 - Longitudinal analyses of catch-at-age data for reconstructing year-class strength, with an application to lake trout (Salvelinus namaycush) in the main basin of Lake Huron","interactions":[],"lastModifiedDate":"2023-01-18T17:23:24.019675","indexId":"70238685","displayToPublicDate":"2022-11-29T06:48:14","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1169,"text":"Canadian Journal of Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Longitudinal analyses of catch-at-age data for reconstructing year-class strength, with an application to lake trout (<i>Salvelinus namaycush</i>) in the main basin of Lake Huron","title":"Longitudinal analyses of catch-at-age data for reconstructing year-class strength, with an application to lake trout (Salvelinus namaycush) in the main basin of Lake Huron","docAbstract":"<div id=\"abstracts\" data-extent=\"frontmatter\"><div class=\"core-container\"><div>We investigated using longitudinal models to reconstruct year-class strength (YCS) from catch-at-age data, with an example application to lake trout (<i>Salvelinus namaycush</i>) in the main basin of Lake Huron. The best model structure depended on the age range used for model implementation. The YCS trajectory from the full age range (3–30 years) was similar to the trajectory from a narrow age range that approximated the age of recruitment to the fishing gears (5–7 years), but YCS estimates from the full age range included additional variations due to time-dependent selectivity and mortality. When using ages younger or older than the likely ages of recruitment, YCS estimates did not represent recruitment abundances and were also biased by trends in age-specific selectivity and mortality across years. Longitudinal YCS estimates are likely more robust than single-age recruitment indices, which are often subject to interannual changes in catchability and selectivity. Our findings provide guidance for future applications of the longitudinal YCS reconstruction that in turn may inform and supplement more comprehensive research and management programs for understanding fish recruitment dynamics.</div></div></div>","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjfas-2022-0140","usgsCitation":"He, J.X., Honsey, A.E., Staples, D.F., Bence, J., and Claramunt, T.L., 2023, Longitudinal analyses of catch-at-age data for reconstructing year-class strength, with an application to lake trout (Salvelinus namaycush) in the main basin of Lake Huron: Canadian Journal of Fisheries and Aquatic Sciences, v. 80, no. 1, p. 183-194, https://doi.org/10.1139/cjfas-2022-0140.","productDescription":"12 p.","startPage":"183","endPage":"194","ipdsId":"IP-141874","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":445195,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1139/cjfas-2022-0140","text":"Publisher Index Page"},{"id":410046,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","otherGeospatial":"Lake Huron","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -84.76832469460116,\n              46.293576597554534\n            ],\n            [\n              -84.76832469460116,\n              42.93351105858869\n            ],\n            [\n              -80.6831455271525,\n              42.93351105858869\n            ],\n            [\n              -80.6831455271525,\n              46.293576597554534\n            ],\n            [\n              -84.76832469460116,\n              46.293576597554534\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"80","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"He, Ji X.","contributorId":181528,"corporation":false,"usgs":false,"family":"He","given":"Ji","email":"","middleInitial":"X.","affiliations":[],"preferred":false,"id":858269,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Honsey, Andrew Edgar 0000-0001-7535-1321","orcid":"https://orcid.org/0000-0001-7535-1321","contributorId":295468,"corporation":false,"usgs":true,"family":"Honsey","given":"Andrew","email":"","middleInitial":"Edgar","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":858270,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Staples, David F.","contributorId":150561,"corporation":false,"usgs":false,"family":"Staples","given":"David","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":858271,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bence, James R.","contributorId":95026,"corporation":false,"usgs":false,"family":"Bence","given":"James R.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":858272,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Claramunt, Tracy L.","contributorId":215447,"corporation":false,"usgs":false,"family":"Claramunt","given":"Tracy","email":"","middleInitial":"L.","affiliations":[{"id":6983,"text":"Michigan DNR","active":true,"usgs":false}],"preferred":false,"id":858273,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70238737,"text":"70238737 - 2023 - Towards a unified drag coefficient formula for quantifying wave energy reduction by salt marshes","interactions":[],"lastModifiedDate":"2022-12-15T16:01:07.181311","indexId":"70238737","displayToPublicDate":"2022-11-27T06:44:07","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1262,"text":"Coastal Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Towards a unified drag coefficient formula for quantifying wave energy reduction by salt marshes","docAbstract":"<div id=\"abstracts\" class=\"Abstracts u-font-serif\"><div id=\"d1e1297\" class=\"abstract author\"><div id=\"d1e1300\"><p id=\"d1e1301\"><span>Coastal regions are susceptible to increasing flood risks amid climate change. Coastal wetlands play an important role in mitigating coastal hazards. Vegetation exerts a drag force to the flow and dampens storm surges and wind waves. The prediction of wave attenuation by vegetation typically relies on a pre-determined drag coefficient&nbsp;</span><span class=\"math\"><span id=\"MathJax-Element-7-Frame\" class=\"MathJax_SVG\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><msub is=&quot;true&quot;><mrow is=&quot;true&quot;><mi is=&quot;true&quot;>C</mi></mrow><mrow is=&quot;true&quot;><mi is=&quot;true&quot;>D</mi></mrow></msub></math>\"><span class=\"MJX_Assistive_MathML\">C<sub>D</sub></span></span></span><span>. Existing&nbsp;</span><span class=\"math\"><span id=\"MathJax-Element-8-Frame\" class=\"MathJax_SVG\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><msub is=&quot;true&quot;><mrow is=&quot;true&quot;><mi is=&quot;true&quot;>C</mi></mrow><mrow is=&quot;true&quot;><mi is=&quot;true&quot;>D</mi></mrow></msub></math>\"><span class=\"MJX_Assistive_MathML\">C<sub>D</sub></span></span></span><span>&nbsp;formulas are subject to vegetation biomechanical properties, especially the flexibility. Accounting for vegetation flexibility through the effective plant height (EPH), we propose and validate a species-independent relationship between&nbsp;</span><span class=\"math\"><span id=\"MathJax-Element-9-Frame\" class=\"MathJax_SVG\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><msub is=&quot;true&quot;><mrow is=&quot;true&quot;><mi is=&quot;true&quot;>C</mi></mrow><mrow is=&quot;true&quot;><mi is=&quot;true&quot;>D</mi></mrow></msub></math>\"><span class=\"MJX_Assistive_MathML\">C<sub>D</sub></span></span></span><span>&nbsp;and the Reynolds number&nbsp;</span><i><span class=\"math\"><span id=\"MathJax-Element-10-Frame\" class=\"MathJax_SVG\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><mrow is=&quot;true&quot;><mi is=&quot;true&quot;>R</mi><mi is=&quot;true&quot;>e</mi></mrow></math>\"><span class=\"MJX_Assistive_MathML\">Re</span></span></span></i><span>&nbsp;based on three independent datasets that cover a wide range of hydrodynamic conditions and vegetation traits. The proposed&nbsp;</span><span class=\"math\"><span id=\"MathJax-Element-11-Frame\" class=\"MathJax_SVG\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><mrow is=&quot;true&quot;><msub is=&quot;true&quot;><mrow is=&quot;true&quot;><mi is=&quot;true&quot;>C</mi></mrow><mrow is=&quot;true&quot;><mi is=&quot;true&quot;>D</mi></mrow></msub><mo linebreak=&quot;goodbreak&quot; linebreakstyle=&quot;after&quot; is=&quot;true&quot;>&amp;#x2212;</mo><mi is=&quot;true&quot;>R</mi><mi is=&quot;true&quot;>e</mi></mrow></math>\"><span class=\"MJX_Assistive_MathML\">C<sub>D</sub>−<i>Re</i></span></span></span><span>&nbsp;relationship, used together with EPH, allows for predicting wave attenuation in salt marshes with high accuracy. Furthermore, a total of 308,000 numerical experiments with diverse wave conditions are conducted using the proposed&nbsp;</span><span class=\"math\"><span id=\"MathJax-Element-12-Frame\" class=\"MathJax_SVG\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><mrow is=&quot;true&quot;><msub is=&quot;true&quot;><mrow is=&quot;true&quot;><mi is=&quot;true&quot;>C</mi></mrow><mrow is=&quot;true&quot;><mi is=&quot;true&quot;>D</mi></mrow></msub><mo linebreak=&quot;goodbreak&quot; linebreakstyle=&quot;after&quot; is=&quot;true&quot;>&amp;#x2212;</mo><mi is=&quot;true&quot;>R</mi><mi is=&quot;true&quot;>e</mi></mrow></math>\"><span class=\"MJX_Assistive_MathML\">C<sub>D</sub>−<i>Re</i></span></span></span><span>&nbsp;relationship and EPH to quantify the wave attenuation capacity of two typical salt mash species:&nbsp;</span><i>Elymus athericus</i><span>&nbsp;(highly flexible) and&nbsp;</span><i>Spartina alterniflora</i><span>&nbsp;(relatively rigid). It is found that wave attenuation is controlled by wave height to water depth ratio and EPH to water depth ratio. When swaying in large waves in shallow to intermediate water depth, a 50-m-long&nbsp;</span><i>Elymus athericus</i><span>&nbsp;field may lose up to 30% capacity for wave attenuation. As wave height increases, highly flexible vegetation causes reduced wave attenuation, whereas relatively rigid vegetation induces increased wave attenuation. The leaf contribution to wave attenuation is highly dependent on the leaf rigidity. It is recommended that leaf properties, especially its Young’s modulus be collected in future field experiments.</span></p></div></div></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.coastaleng.2022.104256","usgsCitation":"Zhu, L., Chen, Q., Ding, Y., Jafari, N., Wang, H., and Johnson, B.D., 2023, Towards a unified drag coefficient formula for quantifying wave energy reduction by salt marshes: Coastal Engineering, v. 180, 104256, 14 p., https://doi.org/10.1016/j.coastaleng.2022.104256.","productDescription":"104256, 14 p.","ipdsId":"IP-121483","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":445202,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.coastaleng.2022.104256","text":"Publisher Index Page"},{"id":410152,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"180","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Zhu, Ling 0000-0003-0261-6848","orcid":"https://orcid.org/0000-0003-0261-6848","contributorId":222169,"corporation":false,"usgs":false,"family":"Zhu","given":"Ling","affiliations":[{"id":38331,"text":"Northeastern University","active":true,"usgs":false}],"preferred":false,"id":858451,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chen, Q. 0000-0002-6540-8758","orcid":"https://orcid.org/0000-0002-6540-8758","contributorId":56532,"corporation":false,"usgs":false,"family":"Chen","given":"Q.","affiliations":[{"id":38331,"text":"Northeastern University","active":true,"usgs":false}],"preferred":true,"id":858452,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ding, Yan","contributorId":299723,"corporation":false,"usgs":false,"family":"Ding","given":"Yan","email":"","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":858453,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jafari, Navid H.","contributorId":214730,"corporation":false,"usgs":false,"family":"Jafari","given":"Navid H.","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":858454,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wang, Hongqing 0000-0002-2977-7732","orcid":"https://orcid.org/0000-0002-2977-7732","contributorId":221902,"corporation":false,"usgs":true,"family":"Wang","given":"Hongqing","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":858455,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Johnson, Bradley D.","contributorId":299724,"corporation":false,"usgs":false,"family":"Johnson","given":"Bradley","email":"","middleInitial":"D.","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":858456,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70238909,"text":"70238909 - 2023 - Addressing detection uncertainty in Bombus affinis (Hymenoptera: Apidae) surveys can improve inferences made from monitoring","interactions":[],"lastModifiedDate":"2023-03-01T17:03:18.36297","indexId":"70238909","displayToPublicDate":"2022-11-22T09:32:15","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1536,"text":"Environmental Entomology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Addressing detection uncertainty in <i>Bombus affinis</i> (Hymenoptera: Apidae) surveys can improve inferences made from monitoring","title":"Addressing detection uncertainty in Bombus affinis (Hymenoptera: Apidae) surveys can improve inferences made from monitoring","docAbstract":"<p><span>The U.S. Fish and Wildlife Service developed national guidelines to track species recovery of the endangered rusty patched bumble bee [</span><i>Bombus affinis</i><span>&nbsp;Cresson (Hymenoptera: Apidae)] and to investigate changes in species occupancy across space and time. As with other native bee monitoring efforts, managers have specifically acknowledged the need to address species detection uncertainty and determine the sampling effort required to infer species absence within sites. We used single-season, single-species occupancy models fit to field data collected in four states to estimate imperfect detection of&nbsp;</span><i>B. affinis</i><span>&nbsp;and to determine the survey effort required to achieve high confidence of species detection. Our analysis revealed a precipitous, seasonal, decline in&nbsp;</span><i>B. affinis</i><span>&nbsp;detection probability throughout the July through September sampling window in 2021. We estimated that six, 30-min surveys conducted in early July are required to achieve a 95% cumulative detection probability, whereas &gt;10 surveys would be required in early August to achieve the same level of confidence. Our analysis also showed&nbsp;</span><i>B. affinis</i><span>&nbsp;was less likely to be detected during hot and humid days and at patches of reduced habitat quality.&nbsp;</span><i>Bombus affinis</i><span>&nbsp;was frequently observed on&nbsp;</span><i>Monarda fistulosa</i><span>&nbsp;(Lamiales: Lamiaceae), followed by [</span><i>Pycnanthemum virginianum</i><span>&nbsp;Rob. and Fernald (Lamiales: Lamiaceae)]</span><i>, Eutrochium maculatum</i><span>&nbsp;Lamont (Asterales: Asteraceae), and&nbsp;</span><i>Veronicastrum virginicum</i><span>&nbsp;Farw. (Lamiales: Plantaginaceae). Although our research is focused on&nbsp;</span><i>B. affinis</i><span>, it is relevant for monitoring other bumble bees of conservation concern, such as&nbsp;</span><i>B. occidentalis</i><span>&nbsp;Greene (Hymenoptera: Apidae) and&nbsp;</span><i>B. terricola</i><span>&nbsp;Kirby (Hymenoptera: Apidae) for which monitoring efforts have been recently initiated and occupancy is a variable of conservation interest.</span></p>","language":"English","publisher":"Oxford Academic","doi":"10.1093/ee/nvac090","usgsCitation":"Otto, C., Schrage, A., Bailey, L., Mola, J.M., Smith, T.A., Pearse, I., Simanonok, S.C., and Grundel, R., 2023, Addressing detection uncertainty in Bombus affinis (Hymenoptera: Apidae) surveys can improve inferences made from monitoring: Environmental Entomology, v. 52, no. 1, p. 108-118, https://doi.org/10.1093/ee/nvac090.","productDescription":"11 p.","startPage":"108","endPage":"118","ipdsId":"IP-142627","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true},{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":445215,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/ee/nvac090","text":"Publisher Index Page"},{"id":435557,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9KCT9HS","text":"USGS data release","linkHelpText":"Dataset: Addressing detection uncertainty in Bombus affinis (Hymenoptera: Apidae) surveys can improve inferences made from monitoring"},{"id":410629,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Illinois, Iowa, Minnesota, Wisconsin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n 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L.","contributorId":229353,"corporation":false,"usgs":false,"family":"Bailey","given":"Larissa L.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":859125,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mola, John Michael 0000-0002-5394-9071","orcid":"https://orcid.org/0000-0002-5394-9071","contributorId":224281,"corporation":false,"usgs":true,"family":"Mola","given":"John","email":"","middleInitial":"Michael","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":859126,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Smith, Tamara A.","contributorId":257977,"corporation":false,"usgs":false,"family":"Smith","given":"Tamara","email":"","middleInitial":"A.","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":859127,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Pearse, Ian S. 0000-0001-7098-0495","orcid":"https://orcid.org/0000-0001-7098-0495","contributorId":211154,"corporation":false,"usgs":true,"family":"Pearse","given":"Ian","middleInitial":"S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":859128,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Simanonok, Stacy C. 0000-0002-0287-3871","orcid":"https://orcid.org/0000-0002-0287-3871","contributorId":229607,"corporation":false,"usgs":true,"family":"Simanonok","given":"Stacy","email":"","middleInitial":"C.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":859129,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Grundel, Ralph 0000-0002-2949-7087 rgrundel@usgs.gov","orcid":"https://orcid.org/0000-0002-2949-7087","contributorId":2444,"corporation":false,"usgs":true,"family":"Grundel","given":"Ralph","email":"rgrundel@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":859130,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70239856,"text":"70239856 - 2023 - Density surface and excursion sets modeling as an approach to estimating population densities","interactions":[],"lastModifiedDate":"2023-01-23T15:11:32.487505","indexId":"70239856","displayToPublicDate":"2022-11-22T08:59:57","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Density surface and excursion sets modeling as an approach to estimating population densities","docAbstract":"<p><span>Effective species management and conservation require knowledge of species distribution and status. We used point-transect distance sampling surveys of the endangered palila (</span><i>Loxioides bailleui</i><span>), a honeycreeper currently found only on the Island of Hawai'i, USA, to generate robust estimates of total abundance and simultaneously model the distribution, abundance, and spatial correlation of the species as a density surface model (DSM). Point-transect distance sampling is a widely applied method to estimate bird densities accounting for imperfect detection probability. For the DSM we used a generalized additive model framework and soap film smoothers to control the effects of boundary features. This modeling approach allowed us to account for imperfect detection and propagate detection probability uncertainty. We compared the uncertainty in palila abundance estimates using standard point-transect distance sampling to estimates from the DSM. The DSM, accounting for both distance-sampling-derived detection probability variance and the generalized additive model density estimate variance, did not improve population estimator precision; however, it provided insight into the species' distribution, density, and uncertainty. We also applied excursion sets analysis to objectively identify areas where the species occurs in high densities. The 2017 global population of &lt;2,000 individuals was limited to an excursion area of 1,500 ha. Our findings can help management and regulatory agencies by simultaneously mapping a species' distribution and density, improving survey protocols, and providing information important to species conservation.</span></p>","language":"English","publisher":"The Wildlife Society","doi":"10.1002/jwmg.22332","usgsCitation":"Camp, R.J., Asing, C.K., Banko, P.C., Berry, L., Brinck, K., Farmer, C., and Genz, A., 2023, Density surface and excursion sets modeling as an approach to estimating population densities: Journal of Wildlife Management, v. 87, no. 2, e22332, 18 p., https://doi.org/10.1002/jwmg.22332.","productDescription":"e22332, 18 p.","ipdsId":"IP-131687","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":445216,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/jwmg.22332","text":"Publisher Index Page"},{"id":412215,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Mauna Kea","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -155.75,\n              20\n            ],\n            [\n              -155.75,\n              19.666\n            ],\n            [\n              -155.25,\n              19.666\n            ],\n            [\n              -155.25,\n              20\n            ],\n            [\n              -155.75,\n              20\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"87","issue":"2","noUsgsAuthors":false,"publicationDate":"2022-11-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Camp, Richard J. 0000-0001-7008-923X rick_camp@usgs.gov","orcid":"https://orcid.org/0000-0001-7008-923X","contributorId":189964,"corporation":false,"usgs":true,"family":"Camp","given":"Richard","email":"rick_camp@usgs.gov","middleInitial":"J.","affiliations":[{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true},{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"preferred":true,"id":862155,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Asing, Chauncey K.","contributorId":272645,"corporation":false,"usgs":false,"family":"Asing","given":"Chauncey","email":"","middleInitial":"K.","affiliations":[{"id":40951,"text":"University of Hawai‘i - Mānoa","active":true,"usgs":false}],"preferred":false,"id":862156,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Banko, Paul C. 0000-0002-6035-9803 pbanko@usgs.gov","orcid":"https://orcid.org/0000-0002-6035-9803","contributorId":3179,"corporation":false,"usgs":true,"family":"Banko","given":"Paul","email":"pbanko@usgs.gov","middleInitial":"C.","affiliations":[{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true},{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"preferred":true,"id":862157,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Berry, Lainie","contributorId":272646,"corporation":false,"usgs":false,"family":"Berry","given":"Lainie","email":"","affiliations":[{"id":56397,"text":"State of Hawai‘i, Division of Forestry and Wildlife","active":true,"usgs":false}],"preferred":false,"id":862158,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Brinck, Kevin W. 0000-0001-7581-2482 kbrinck@usgs.gov","orcid":"https://orcid.org/0000-0001-7581-2482","contributorId":3847,"corporation":false,"usgs":true,"family":"Brinck","given":"Kevin W.","email":"kbrinck@usgs.gov","affiliations":[],"preferred":false,"id":862159,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Farmer, Chris","contributorId":150179,"corporation":false,"usgs":false,"family":"Farmer","given":"Chris","affiliations":[{"id":17929,"text":"American Bird Conservancy","active":true,"usgs":false}],"preferred":false,"id":862160,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Genz, Ayesha 0000-0002-2916-1436","orcid":"https://orcid.org/0000-0002-2916-1436","contributorId":196671,"corporation":false,"usgs":false,"family":"Genz","given":"Ayesha","email":"","affiliations":[],"preferred":false,"id":862161,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70238616,"text":"70238616 - 2023 - Geophysical data provide three dimensional insights into porphyry copper systems in the Silverton caldera, Colorado, USA","interactions":[],"lastModifiedDate":"2022-12-01T14:03:23.274569","indexId":"70238616","displayToPublicDate":"2022-11-22T07:56:08","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2954,"text":"Ore Geology Reviews","active":true,"publicationSubtype":{"id":10}},"title":"Geophysical data provide three dimensional insights into porphyry copper systems in the Silverton caldera, Colorado, USA","docAbstract":"<p><span>The Silverton caldera in southwest Colorado, USA hosts polymetallic veins and pervasively altered rocks indicative of porphyry copper systems. Nearly a kilometer of erosion has exposed multiple levels of the hydrothermal systems from shallow lithocaps down to quartz-sericite-pyrite veins. New airborne electromagnetic and magnetic survey data are integrated with previous alteration mapping and porphyry models to show the subsurface geophysical response of shallow to deep levels of the porphyry system. Qualitative map views show lateral changes in the magnetization and resistivity of the hydrothermally altered rocks. The volcanic terrain exhibits high magnetization and high amplitude anomalies map near-surface plutonic rocks associated with porphyry systems. Magnetic susceptibility measurements on outcrops of hydrothermally altered rocks indicate magnetite content decreases upward and outward from the source intrusions where magnetic anomaly lows are observed over the lithocaps. The resistivity maps highlight hydrothermal alteration as resistivity lows with exception being rocks having propylitic alteration. Quantitative resistivity models show low resistivity zones with an apparent thickness around 50–150&nbsp;m beneath quartz-sericite-pyrite veins interpreted to be the result of supergene processes that may continue today, and the calculated magnetic source depths occur near the top of this zone. The resistivity models also show rocks having propylitic, silicic, and quartz-alunite-pyrophyllite assemblages exhibit high resistivity with depth, and argillic alteration assemblages had high resistivity due to high quartz content. This integrated approach presented in a three-dimensional environment provides guidance when exploring for porphyry copper systems in less exposed terrains.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.oregeorev.2022.105223","usgsCitation":"Anderson, E., Yager, D., Deszcz-Pan, M., Hoogenboom, B.E., Rodriguez, B.D., and Smith, B., 2023, Geophysical data provide three dimensional insights into porphyry copper systems in the Silverton caldera, Colorado, USA: Ore Geology Reviews, v. 152, 105223, 22 p., https://doi.org/10.1016/j.oregeorev.2022.105223.","productDescription":"105223, 22 p.","ipdsId":"IP-139706","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":445219,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.oregeorev.2022.105223","text":"Publisher Index Page"},{"id":435558,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P99JRNU2","text":"USGS data release","linkHelpText":"Magnetic susceptibility measurements on hydrothermally altered rocks in the Silverton caldera, southwest Colorado"},{"id":409918,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Silverton caldera","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -108.41198468872895,\n              38.21942984890151\n            ],\n            [\n              -108.41198468872895,\n              37.34604421849235\n            ],\n            [\n              -107.19637481288558,\n              37.34604421849235\n            ],\n            [\n              -107.19637481288558,\n              38.21942984890151\n            ],\n            [\n              -108.41198468872895,\n              38.21942984890151\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"152","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Anderson, Eric D. 0000-0002-0138-6166","orcid":"https://orcid.org/0000-0002-0138-6166","contributorId":202072,"corporation":false,"usgs":true,"family":"Anderson","given":"Eric D.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":858106,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yager, Douglas 0000-0001-5074-4022","orcid":"https://orcid.org/0000-0001-5074-4022","contributorId":202073,"corporation":false,"usgs":true,"family":"Yager","given":"Douglas","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":858107,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Deszcz-Pan, Maria 0000-0002-6298-5314 maryla@usgs.gov","orcid":"https://orcid.org/0000-0002-6298-5314","contributorId":1263,"corporation":false,"usgs":true,"family":"Deszcz-Pan","given":"Maria","email":"maryla@usgs.gov","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":858108,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hoogenboom, Bennett Eugene 0000-0001-8096-3533","orcid":"https://orcid.org/0000-0001-8096-3533","contributorId":239871,"corporation":false,"usgs":true,"family":"Hoogenboom","given":"Bennett","email":"","middleInitial":"Eugene","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":858109,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rodriguez, Brian D. 0000-0002-2263-611X brod@usgs.gov","orcid":"https://orcid.org/0000-0002-2263-611X","contributorId":836,"corporation":false,"usgs":true,"family":"Rodriguez","given":"Brian","email":"brod@usgs.gov","middleInitial":"D.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":858110,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Smith, Bruce 0000-0002-1643-2997","orcid":"https://orcid.org/0000-0002-1643-2997","contributorId":214824,"corporation":false,"usgs":true,"family":"Smith","given":"Bruce","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":858111,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70242079,"text":"70242079 - 2023 - Impact of SARS-CoV-2 vaccination of children ages 5–11 years on COVID-19 disease burden and resilience to new variants in the United States, November 2021–March 2022: A multi-model study","interactions":[],"lastModifiedDate":"2023-04-06T14:06:36.348726","indexId":"70242079","displayToPublicDate":"2022-11-22T07:04:22","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":13786,"text":"The Lancet Regional Health - Americas","active":true,"publicationSubtype":{"id":10}},"title":"Impact of SARS-CoV-2 vaccination of children ages 5–11 years on COVID-19 disease burden and resilience to new variants in the United States, November 2021–March 2022: A multi-model study","docAbstract":"<div id=\"abssec0010\"><h3 id=\"sectitle0015\" class=\"u-h4 u-margin-m-top u-margin-xs-bottom\">Background</h3><p id=\"abspara0010\">The COVID-19 Scenario Modeling Hub convened nine modeling teams to project the impact of expanding SARS-CoV-2 vaccination to children aged 5–11 years on COVID-19 burden and resilience against variant strains.</p></div><div id=\"abssec0015\"><h3 id=\"sectitle0020\" class=\"u-h4 u-margin-m-top u-margin-xs-bottom\">Methods</h3><p id=\"abspara0015\">Teams contributed state- and national-level weekly projections of cases, hospitalizations, and deaths in the United States from September 12, 2021 to March 12, 2022. Four scenarios covered all combinations of 1) vaccination (or not) of children aged 5–11 years (starting November 1, 2021), and 2) emergence (or not) of a variant more transmissible than the Delta variant (emerging November 15, 2021). Individual team projections were linearly pooled. The effect of childhood vaccination on overall and age-specific outcomes was estimated using meta-analyses.</p></div><div id=\"abssec0020\"><h3 id=\"sectitle0025\" class=\"u-h4 u-margin-m-top u-margin-xs-bottom\">Findings</h3><p id=\"abspara0020\">Assuming that a new variant would not emerge, all-age COVID-19 outcomes were projected to decrease nationally through mid-March 2022. In this setting, vaccination of children 5–11 years old was associated with reductions in projections for all-age cumulative cases (7.2%, mean incidence ratio [IR] 0.928, 95% confidence interval [CI] 0.880–0.977), hospitalizations (8.7%, mean IR 0.913, 95% CI 0.834–0.992), and deaths (9.2%, mean IR 0.908, 95% CI 0.797–1.020) compared with scenarios without childhood vaccination. Vaccine benefits increased for scenarios including a hypothesized more transmissible variant, assuming similar vaccine effectiveness. Projected relative reductions in cumulative outcomes were larger for children than for the entire population. State-level variation was observed.</p></div><div id=\"abssec0025\"><h3 id=\"sectitle0030\" class=\"u-h4 u-margin-m-top u-margin-xs-bottom\">Interpretation</h3><p id=\"abspara0025\">Given the scenario assumptions (defined before the emergence of Omicron), expanding vaccination to children 5–11 years old would provide measurable direct benefits, as well as indirect benefits to the all-age U.S. population, including resilience to more transmissible variants.</p></div><div id=\"abssec0030\"><h3 id=\"sectitle0035\" class=\"u-h4 u-margin-m-top u-margin-xs-bottom\">Funding</h3><p id=\"abspara0030\">Various (see acknowledgments).</p></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.lana.2022.100398","usgsCitation":"Borchering, R.K., Mullany, L.C., Howerton, E., Chinazzi, M., Smith, C.P., Qin, M., Reich, N.G., Contamin, L., Levander, J., Kerr, J., Espino, J., Hochheiser, H., Lovett, K., Kinsey, M., Tallaksen, K., Wilson, S., Shin, L., Lemaitre, J., Dent Hulse, J., Kaminsky, 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mrunge@usgs.gov","orcid":"https://orcid.org/0000-0002-8081-536X","contributorId":3358,"corporation":false,"usgs":true,"family":"Runge","given":"Michael","email":"mrunge@usgs.gov","middleInitial":"C.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":868776,"contributorType":{"id":1,"text":"Authors"},"rank":61},{"text":"Viboud, Cecile 0000-0003-3243-4711","orcid":"https://orcid.org/0000-0003-3243-4711","contributorId":258034,"corporation":false,"usgs":false,"family":"Viboud","given":"Cecile","email":"","affiliations":[{"id":52216,"text":"National Institutes of Health Fogarty International Center","active":true,"usgs":false}],"preferred":false,"id":868875,"contributorType":{"id":1,"text":"Authors"},"rank":62},{"text":"Lessler, Justin","contributorId":258042,"corporation":false,"usgs":false,"family":"Lessler","given":"Justin","email":"","affiliations":[{"id":36717,"text":"Johns Hopkins 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,{"id":70256618,"text":"70256618 - 2023 - Accounting for spatial heterogeneity in visual obstruction in line-transect distance sampling of gopher tortoises","interactions":[],"lastModifiedDate":"2024-08-27T14:47:33.790307","indexId":"70256618","displayToPublicDate":"2022-11-21T09:38:37","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Accounting for spatial heterogeneity in visual obstruction in line-transect distance sampling of gopher tortoises","docAbstract":"<p><span>Line-transect distance sampling (LTDS) surveys are commonly used to estimate abundance of animals or objects. In terrestrial LTDS surveys of gopher tortoise (</span><i>Gopherus polyphemus</i><span>) burrows, the presence of ground-level vegetation substantially decreases detection of burrows of all sizes, but no field or analytical methods exist to control for spatially heterogeneous vegetation obstruction as a source of variation in detection. We propose the addition of a simple measurement of ground-level vegetation that serves as a covariate for the detection function. We present a Bayesian hierarchical model in which covariates burrow width and nearby vegetation height help to account for detection bias and improve precision of estimated density. We investigate the performance of this covariate by simulation and by using real LTDS data collected before and after application of prescribed fire. We collected data in 2018 at the Jones Center at Ichauway in Newton, Georgia, USA. Across all simulations, our model including both covariates produced the most accurate density point estimates of any of the models tested. For our case study, our Bayesian model with vegetation covariates tended to produce similar estimates of density before and after burns. Our study indicates that any level of spatial variation in vegetation obstruction decreases detection of burrows and may lead to underestimation in population size (≤68%) and proportion of individuals with small burrow sizes (≤32%) when not considered during analysis. Our work is extensible to other terrestrial sampling efforts where systematic measurement of a spatially distributed obstructing feature is feasible during the LTDS survey.</span></p>","language":"English","publisher":"The Wildlife Society","doi":"10.1002/jwmg.22338","usgsCitation":"Gaya, H.E., Smith, L., and Moore, C.T., 2023, Accounting for spatial heterogeneity in visual obstruction in line-transect distance sampling of gopher tortoises: Journal of Wildlife Management, v. 87, no. 2, e22338, 18 p., https://doi.org/10.1002/jwmg.22338.","productDescription":"e22338, 18 p.","ipdsId":"IP-138680","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":445229,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/jwmg.22338","text":"Publisher Index Page"},{"id":433197,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Georgia","county":"Baker County","city":"Newton","otherGeospatial":"Jones Center at Ichauway","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -84.5442497881046,\n              31.26474310157134\n            ],\n            [\n              -84.5442497881046,\n              31.19461870802469\n            ],\n            [\n              -84.4520518322151,\n              31.19461870802469\n            ],\n            [\n              -84.4520518322151,\n              31.26474310157134\n            ],\n            [\n              -84.5442497881046,\n              31.26474310157134\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"87","issue":"2","noUsgsAuthors":false,"publicationDate":"2022-11-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Gaya, Heather E.","contributorId":341387,"corporation":false,"usgs":false,"family":"Gaya","given":"Heather","email":"","middleInitial":"E.","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":908335,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smith, Lora L.","contributorId":341388,"corporation":false,"usgs":false,"family":"Smith","given":"Lora L.","affiliations":[{"id":81731,"text":"Jones Center at Ichauway","active":true,"usgs":false}],"preferred":false,"id":908336,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Moore, Clinton T. 0000-0002-6053-2880 cmoore@usgs.gov","orcid":"https://orcid.org/0000-0002-6053-2880","contributorId":3643,"corporation":false,"usgs":true,"family":"Moore","given":"Clinton","email":"cmoore@usgs.gov","middleInitial":"T.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":908337,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70242127,"text":"70242127 - 2023 - High‐precision characterization of seismicity from the 2022 Hunga Tonga‐Hunga Ha'apai volcanic eruption","interactions":[],"lastModifiedDate":"2023-04-07T14:13:17.091903","indexId":"70242127","displayToPublicDate":"2022-11-18T08:55:02","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"High‐precision characterization of seismicity from the 2022 Hunga Tonga‐Hunga Ha'apai volcanic eruption","docAbstract":"<p><span>The earthquake swarm accompanying the January 2022 Hunga Tonga‐Hunga Ha'apai (HTHH) volcanic eruption includes a large number of posteruptive moderate‐magnitude seismic events and presents a unique opportunity to use remote monitoring methods to characterize and compare seismic activity with other historical caldera‐forming eruptions. We compute improved epicentroid locations, magnitudes, and regional moment tensors of seismic events from this earthquake swarm using regional to teleseismic surface‐wave cross correlation and waveform modeling. Precise relative locations of 91 seismic events derived from 59,047 intermediate‐period Rayleigh‐ and Love‐wave cross‐correlation measurements collapse into a small area surrounding the volcano and exhibit a southeastern time‐dependent migration. Regional moment tensors and observed waveforms indicate that these events have a similar mechanism and exhibit a strong positive compensated linear vector dipole component. Precise relative magnitudes agree with regional moment tensor moment magnitude (</span><i><span class=\"inline-formula no-formula-id\">⁠<span id=\"MathJax-Element-1-Frame\" class=\"MathJax\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><msub xmlns=&quot;&quot;><mi>M</mi><mi mathvariant=&quot;normal&quot;>w</mi></msub></math>\"><span id=\"MathJax-Span-1\" class=\"math\"><span><span id=\"MathJax-Span-2\" class=\"mrow\"><span id=\"MathJax-Span-3\" class=\"msub\"><span id=\"MathJax-Span-4\" class=\"mi\">M</span><sub><span id=\"MathJax-Span-5\" class=\"mi\">w</span></sub></span></span></span></span></span><sub>⁠</sub></span></i><span>) estimates while also showing that event sizes and frequency increase during the days after the eruption followed by a period of several weeks of less frequent seismicity of a similar size. The combined information from visual observation and early geologic models indicate that the observed seismicity may be the result of a complex series of events that occurred after the explosive eruption on 15 January, possibly involving rapid resupply of the magma chamber shortly after the eruption and additional faulting and instability in the following weeks. In addition, we identify and characterize an&nbsp;</span><i><span class=\"inline-formula no-formula-id\"><span id=\"MathJax-Element-2-Frame\" class=\"MathJax\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><msub xmlns=&quot;&quot;><mi>M</mi><mi mathvariant=&quot;normal&quot;>w</mi></msub></math>\"><span id=\"MathJax-Span-6\" class=\"math\"><span><span id=\"MathJax-Span-7\" class=\"mrow\"><span id=\"MathJax-Span-8\" class=\"msub\"><span id=\"MathJax-Span-9\" class=\"mi\">M</span><sub><span id=\"MathJax-Span-10\" class=\"mi\">w</span></sub></span></span></span></span></span></span></i><span>&nbsp;4.5 event five days before the paroxysmal explosion on 15 January, indicating that additional seismic events preceding the main eruption could have been identified with improved local monitoring. Our analysis of the HTHH eruption sequence demonstrates the value of potentially utilizing teleseismic surface‐wave cross correlation and waveform modeling methods to assist in the detailed analysis of remote volcanic eruption sequences.</span></p>","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220220250","usgsCitation":"Kintner, J.A., Yeck, W.L., Earle, P.S., Prejean, S., and Pesicek, J., 2023, High‐precision characterization of seismicity from the 2022 Hunga Tonga‐Hunga Ha'apai volcanic eruption: Seismological Research Letters, v. 94, no. 2A, p. 589-602, https://doi.org/10.1785/0220220250.","productDescription":"14 p.","startPage":"589","endPage":"602","ipdsId":"IP-145475","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":445235,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.osti.gov/biblio/1992265","text":"External Repository"},{"id":415417,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Fiji, Samoa, Tonga","otherGeospatial":"Futuna","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -168.88204698275342,\n              -12.5\n            ],\n            [\n              -179.9,\n              -12.5\n            ],\n            [\n              -179.9,\n              -22\n            ],\n            [\n              -168.88204698275342,\n              -22\n            ],\n            [\n              -168.88204698275342,\n              -12.5\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              176.54085286699615,\n              -16.089119614726172\n            ],\n            [\n              176.54085286699615,\n              -19.570942559633565\n            ],\n            [\n              179.9852885549384,\n              -19.570942559633565\n            ],\n            [\n              179.9852885549384,\n              -16.089119614726172\n            ],\n            [\n              176.54085286699615,\n              -16.089119614726172\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"94","issue":"2A","noUsgsAuthors":false,"publicationDate":"2022-11-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Kintner, Jonas A. 0000-0002-0739-6349","orcid":"https://orcid.org/0000-0002-0739-6349","contributorId":304028,"corporation":false,"usgs":false,"family":"Kintner","given":"Jonas","email":"","middleInitial":"A.","affiliations":[{"id":13447,"text":"Los Alamos National Laboratory","active":true,"usgs":false}],"preferred":false,"id":868957,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yeck, William L. 0000-0002-2801-8873 wyeck@usgs.gov","orcid":"https://orcid.org/0000-0002-2801-8873","contributorId":147558,"corporation":false,"usgs":true,"family":"Yeck","given":"William","email":"wyeck@usgs.gov","middleInitial":"L.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":309,"text":"Geology and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":868958,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Earle, Paul S. 0000-0002-3500-017X pearle@usgs.gov","orcid":"https://orcid.org/0000-0002-3500-017X","contributorId":173551,"corporation":false,"usgs":true,"family":"Earle","given":"Paul","email":"pearle@usgs.gov","middleInitial":"S.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":868959,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Prejean, Stephanie 0000-0003-0510-1989 sprejean@usgs.gov","orcid":"https://orcid.org/0000-0003-0510-1989","contributorId":172404,"corporation":false,"usgs":true,"family":"Prejean","given":"Stephanie","email":"sprejean@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":868960,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pesicek, Jeremy 0000-0001-7964-5845 jpesicek@usgs.gov","orcid":"https://orcid.org/0000-0001-7964-5845","contributorId":173180,"corporation":false,"usgs":true,"family":"Pesicek","given":"Jeremy","email":"jpesicek@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":868961,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70240255,"text":"70240255 - 2023 - Evaluations of Lagrangian egg drift models: From a laboratory flume to large channelized rivers","interactions":[],"lastModifiedDate":"2023-02-02T16:20:30.401536","indexId":"70240255","displayToPublicDate":"2022-11-18T08:17:43","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1458,"text":"Ecological Modelling","active":true,"publicationSubtype":{"id":10}},"title":"Evaluations of Lagrangian egg drift models: From a laboratory flume to large channelized rivers","docAbstract":"<p>To help better interpret computational models in predicting drift of carp eggs in rivers, we present a series of model assessments for the longitudinal egg dispersion. Two three-dimensional Lagrangian particle tracking models, SDrift and FluEgg, are evaluated in a series of channels with increasing complexity. The model evaluation demonstrates that both models are able to accommodate channel complexity and provide a wide range of dispersion coefficients: <i>K<sub>l</sub></i><span>=</span><i>0</i><span>(1 − 100)</span><i>Hu<sub>∗</sub></i> with <i>H</i> being water depth and <i>u<sub>∗</sub></i> being shear velocity. In a straight channel with <i>K<sub>l</sub></i><span>=</span><i>0</i><span>(1)</span><i>Hu<sub>∗</sub></i> SDrift predicts weaker longitudinal dispersion than FluEgg in the early stage as a result of weak vertical mixing associated with smooth wall turbulence. With sufficient time, SDrift and FluEgg predict similar egg dispersion, accounting for the differential advection due to the vertical velocity profile. In an idealized curved channel with <i>K<sub>l</sub></i><span>=</span><i>0</i><span>(10)</span><i>Hu<sub>∗</sub></i>, dispersion is driven by both vertical and transverse velocity profiles. SDrift yields slightly larger dispersion coefficients than FluEgg. In a real river with channel-training structures and having <i>K<sub>l</sub></i><span>=</span><i>0</i><span>(100)</span><i>Hu<sub>∗</sub></i>&nbsp;SDrift predicts a stronger longitudinal dispersion than FluEgg due to substantial local turbulent eddies and velocity gradients. To summarize, FluEgg shows good performance in capturing dispersion due to vertical velocity profiles and cross-channel velocity gradients. SDrift shows excellent model capabilities of revealing various dispersion mechanisms in addition to the vertical and cross-channel velocity variations. They include the initial turbulent diffusion stage with growing dispersion coefficients and strong dispersion due to in-stream hydraulic structures and localized turbulence.</p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolmodel.2022.110200","usgsCitation":"Li, G., Elliott, C.M., Call, B., Chapman, D., Jacobson, R.B., and Wang, B., 2023, Evaluations of Lagrangian egg drift models: From a laboratory flume to large channelized rivers: Ecological Modelling, v. 475, 110200, 11 p., https://doi.org/10.1016/j.ecolmodel.2022.110200.","productDescription":"110200, 11 p.","ipdsId":"IP-144141","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":412623,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Missouri","city":"Lexington","otherGeospatial":"Missouri River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -93.87382488800966,\n              39.22446045728665\n            ],\n            [\n              -93.87382488800966,\n              39.18910122319653\n            ],\n            [\n              -93.76470370918322,\n              39.18910122319653\n            ],\n            [\n              -93.76470370918322,\n              39.22446045728665\n            ],\n            [\n              -93.87382488800966,\n              39.22446045728665\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"475","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Li, Geng","contributorId":298636,"corporation":false,"usgs":false,"family":"Li","given":"Geng","email":"","affiliations":[{"id":6754,"text":"University of Missouri","active":true,"usgs":false}],"preferred":false,"id":863099,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Elliott, Caroline M. 0000-0002-9190-7462 celliott@usgs.gov","orcid":"https://orcid.org/0000-0002-9190-7462","contributorId":2380,"corporation":false,"usgs":true,"family":"Elliott","given":"Caroline","email":"celliott@usgs.gov","middleInitial":"M.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":863100,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Call, Bruce 0000-0001-9064-2231","orcid":"https://orcid.org/0000-0001-9064-2231","contributorId":217707,"corporation":false,"usgs":true,"family":"Call","given":"Bruce","email":"","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":863101,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Chapman, Duane 0000-0002-1086-8853 dchapman@usgs.gov","orcid":"https://orcid.org/0000-0002-1086-8853","contributorId":1291,"corporation":false,"usgs":true,"family":"Chapman","given":"Duane","email":"dchapman@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true},{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":863102,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jacobson, Robert B. 0000-0002-8368-2064 rjacobson@usgs.gov","orcid":"https://orcid.org/0000-0002-8368-2064","contributorId":1289,"corporation":false,"usgs":true,"family":"Jacobson","given":"Robert","email":"rjacobson@usgs.gov","middleInitial":"B.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":863103,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wang, Bin","contributorId":298637,"corporation":false,"usgs":false,"family":"Wang","given":"Bin","affiliations":[{"id":6754,"text":"University of Missouri","active":true,"usgs":false}],"preferred":false,"id":863104,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70250311,"text":"70250311 - 2023 - A practical guide to understanding and validating complex models using data simulations","interactions":[],"lastModifiedDate":"2023-12-01T13:10:09.553573","indexId":"70250311","displayToPublicDate":"2022-11-18T07:07:42","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2717,"text":"Methods in Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"A practical guide to understanding and validating complex models using data simulations","docAbstract":"<ol class=\"\"><li>Biologists routinely fit novel and complex statistical models to push the limits of our understanding. Examples include, but are not limited to, flexible Bayesian approaches (e.g. BUGS, stan), frequentist and likelihood-based approaches (e.g. packages<span>&nbsp;</span><span class=\"smallCaps\">lme4</span>) and machine learning methods.</li><li>These software and programs afford the user greater control and flexibility in tailoring complex hierarchical models. However, this level of control and flexibility places a higher degree of responsibility on the user to evaluate the robustness of their statistical inference. To determine how often biologists are running model diagnostics on hierarchical models, we reviewed 50 recently published papers in 2021 in the journal<span>&nbsp;</span><i>Nature Ecology &amp; Evolution</i>, and we found that the majority of published papers did<span>&nbsp;</span><i>not</i><span>&nbsp;</span>report any validation of their hierarchical models, making it difficult for the reader to assess the robustness of their inference. This lack of reporting likely stems from a lack of standardized guidance for best practices and standard methods.</li><li>Here, we provide a guide to understanding and validating complex models using data simulations. To determine how often biologists use data simulation techniques, we also reviewed 50 recently published papers in 2021 in the journal<span>&nbsp;</span><i>Methods Ecology &amp; Evolution</i>. We found that 78% of the papers that proposed a new estimation technique, package or model used simulations or generated data in some capacity (18 of 23 papers); but very few of those papers (5 of 23 papers) included either a demonstration that the code could recover realistic estimates for a dataset with known parameters or a demonstration of the statistical properties of the approach. To distil the variety of simulations techniques and their uses, we provide a taxonomy of simulation studies based on the intended inference. We also encourage authors to include a basic validation study whenever novel statistical models are used, which in general, is easy to implement.</li><li>Simulating data helps a researcher gain a deeper understanding of the models and their assumptions and establish the reliability of their estimation approaches. Wider adoption of data simulations by biologists can improve statistical inference, reliability and open science practices.</li></ol>","language":"English","publisher":"British Ecological Society","doi":"10.1111/2041-210X.14030","usgsCitation":"DiRenzo, G.V., Hanks, E., and Miller, D., 2023, A practical guide to understanding and validating complex models using data simulations: Methods in Ecology and Evolution, v. 14, no. 1, p. 203-217, https://doi.org/10.1111/2041-210X.14030.","productDescription":"15 p.","startPage":"203","endPage":"217","ipdsId":"IP-138387","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":445239,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/2041-210x.14030","text":"Publisher Index Page"},{"id":435559,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P99B0IJ7","text":"USGS data release","linkHelpText":"Simulations to understand and validate models"},{"id":423142,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"14","issue":"1","noUsgsAuthors":false,"publicationDate":"2022-11-18","publicationStatus":"PW","contributors":{"authors":[{"text":"DiRenzo, Graziella Vittoria 0000-0001-5264-4762","orcid":"https://orcid.org/0000-0001-5264-4762","contributorId":243404,"corporation":false,"usgs":true,"family":"DiRenzo","given":"Graziella","email":"","middleInitial":"Vittoria","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":889406,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hanks, Ephraim","contributorId":332094,"corporation":false,"usgs":false,"family":"Hanks","given":"Ephraim","affiliations":[{"id":7260,"text":"Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":889407,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Miller, David A. W.","contributorId":332095,"corporation":false,"usgs":false,"family":"Miller","given":"David A. W.","affiliations":[{"id":7260,"text":"Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":889408,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70238803,"text":"70238803 - 2023 - A review of supervised learning methods for classifying animal behavioural states from environmental features","interactions":[],"lastModifiedDate":"2023-01-18T17:24:36.527931","indexId":"70238803","displayToPublicDate":"2022-11-16T07:46:42","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2717,"text":"Methods in Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"A review of supervised learning methods for classifying animal behavioural states from environmental features","docAbstract":"<div class=\"article-section__content en main\"><ol class=\"\"><li>Accurately predicting behavioural modes of animals in response to environmental features is important for ecology and conservation. Supervised learning (SL) methods are increasingly common in animal movement ecology for classifying behavioural modes. However, few examples exist of applying SL to classify polytomous animal behaviour from environmental features especially in the context of millions of animal observations.</li><li>We review SL methods (weighted<span>&nbsp;</span><i>k</i>-nearest neighbours; neural nets; random forests; and boosted classification trees with XGBoost) for classifying polytomous animal behaviour from environmental predictors. We also describe tuning parameter selection and assessment strategies, approaches for visualizing relationships between predictors and class outputs, and computational considerations. We demonstrate these methods by predicting three categories of risk to bald eagles from colliding with wind turbines using, as predictors, 12 environmental state features associated with 1.7 million GPS telemetry data points from 57 eagles.</li><li>Of the SL methods we considered, XGBoost yielded the most accurate model with 86.2% classification accuracy and pairwise-averaged area under the ROC curve of 90.6. Computational time of XGBoost scaled better to large data than any other SL method. We also show how SHAP values integrated in the R package (<span class=\"smallCaps\">xgboost</span>) facilitate investigation of variable relationships and importance.</li><li>For big data applications, XGBoost appears to provide superior classification accuracy and computational efficiency. Our results suggest XGBoost should be considered as an early modelling option in situations where the intent is to classify millions of animal behaviour observations from environmental predictors and to understand relationships between those predictors and movement behaviours. We also offer a tutorial to assist researchers in implementing this method.</li></ol></div>","language":"English","publisher":"British Ecological Society","doi":"10.1111/2041-210X.14019","usgsCitation":"Bergen, S., Huso, M., Duerr, A.E., Braham, M.A., Schmuecker, S., Miller, T.A., and Katzner, T., 2023, A review of supervised learning methods for classifying animal behavioural states from environmental features: Methods in Ecology and Evolution, v. 14, no. 1, p. 189-202, https://doi.org/10.1111/2041-210X.14019.","productDescription":"14 p.","startPage":"189","endPage":"202","ipdsId":"IP-137834","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":445244,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/2041-210x.14019","text":"Publisher Index Page"},{"id":410360,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"14","issue":"1","noUsgsAuthors":false,"publicationDate":"2022-11-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Bergen, Silas","contributorId":288432,"corporation":false,"usgs":false,"family":"Bergen","given":"Silas","email":"","affiliations":[{"id":61757,"text":"Winona State University","active":true,"usgs":false}],"preferred":false,"id":858757,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Huso, Manuela 0000-0003-4687-6625 mhuso@usgs.gov","orcid":"https://orcid.org/0000-0003-4687-6625","contributorId":223969,"corporation":false,"usgs":true,"family":"Huso","given":"Manuela","email":"mhuso@usgs.gov","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":858758,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Duerr, Adam E.","contributorId":102324,"corporation":false,"usgs":true,"family":"Duerr","given":"Adam","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":858759,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Braham, Missy A","contributorId":288433,"corporation":false,"usgs":false,"family":"Braham","given":"Missy","email":"","middleInitial":"A","affiliations":[{"id":61759,"text":"Conservation Science Global, Inc.","active":true,"usgs":false}],"preferred":false,"id":858760,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schmuecker, Sara","contributorId":213247,"corporation":false,"usgs":false,"family":"Schmuecker","given":"Sara","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":858761,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Miller, Tricia A.","contributorId":190591,"corporation":false,"usgs":false,"family":"Miller","given":"Tricia","email":"","middleInitial":"A.","affiliations":[{"id":16210,"text":"Division of Forestry and Natural Resources, West Virginia University","active":true,"usgs":false}],"preferred":false,"id":858762,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Katzner, Todd E. 0000-0003-4503-8435 tkatzner@usgs.gov","orcid":"https://orcid.org/0000-0003-4503-8435","contributorId":191353,"corporation":false,"usgs":true,"family":"Katzner","given":"Todd E.","email":"tkatzner@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":858763,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70263636,"text":"70263636 - 2023 - Rupture scenarios for the 3 June 1770 Haiti earthquake","interactions":[],"lastModifiedDate":"2025-02-18T15:35:58.705398","indexId":"70263636","displayToPublicDate":"2022-11-15T09:30:16","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Rupture scenarios for the 3 June 1770 Haiti earthquake","docAbstract":"<p><span>The 2010&nbsp;</span><strong>M</strong><span>&nbsp;7.0 Haiti earthquake provided the impetus to reconsider historical earthquakes in Hispaniola (</span><a class=\"link link-ref xref-bibr\" data-modal-source-id=\"rf11\">Bakun<span>&nbsp;</span><i>et&nbsp;al.</i>, 2012</a><span>). That earthquake also shed new light on complex fault systems along Haiti’s southern peninsula (</span><a class=\"link link-ref xref-bibr\" data-modal-source-id=\"rf30\">Douilly<span>&nbsp;</span><i>et&nbsp;al.</i>, 2013</a><span>;&nbsp;</span><a class=\"link link-ref xref-bibr\" data-modal-source-id=\"rf104\">Saint Fleur<span>&nbsp;</span><i>et&nbsp;al.</i>, 2015</a><span>). Recently, the 2021&nbsp;</span><strong>M</strong><span>&nbsp;7.2 Nippes earthquake (</span><a class=\"link link-ref xref-bibr\" data-modal-source-id=\"rf22\">Calais<span>&nbsp;</span><i>et&nbsp;al.</i>, 2022</a><span>;&nbsp;</span><a class=\"link link-ref xref-bibr\" data-modal-source-id=\"rf31\">Douilly<span>&nbsp;</span><i>et&nbsp;al.</i>, 2022</a><span>), and a recent study reconsidering the 1860 sequence (</span><a class=\"link link-ref xref-bibr\" data-modal-source-id=\"rf75\">Martin<span>&nbsp;</span><i>et&nbsp;al.</i>, 2022</a><span>) further underscored the complexity of fault systems and large earthquake ruptures along the peninsula. Motivated by these studies and recent geological investigations (</span><a class=\"link link-ref xref-bibr\" data-modal-source-id=\"rf98\">Prentice<span>&nbsp;</span><i>et&nbsp;al.</i>, 2010</a><span>;&nbsp;</span><a class=\"link link-ref xref-bibr\" data-modal-source-id=\"rf105\">Saint Fleur<span>&nbsp;</span><i>et&nbsp;al.</i>, 2020</a><span>), we reconsider the 3 June 1770 Haiti earthquake to explore the conventional assumption that it was the last major (</span><strong>M</strong><span>&nbsp;≥7.5) earthquake along the Enriquillo–Plantain Garden fault (EPGF). Accounts provide compelling evidence for substantial liquefaction in the Cul‐de‐Sac plain, one or more likely landslide‐driven tsunami in Gonaïves Bay, and extensive landsliding that created at least three documented landslide dams. We consider three end‐member rupture scenarios that are consistent with available constraints: two scenarios with&nbsp;</span><strong>M</strong><span>&nbsp;7.7 and rupture lengths of 150–170&nbsp;km, and one scenario with a ∼90&nbsp;km rupture and&nbsp;</span><strong>M</strong><span>&nbsp;7.5. Absent future work to identify and date paleoevents along the southern peninsula, none of these scenarios can be ruled out. Our preferred rupture model extends from the Miragoâne pull‐apart to near la Selle mountain, with a rupture length of 127&nbsp;km,&nbsp;</span><strong>M</strong><span>&nbsp;7.6, and a high stress drop. Rupture could have been on the EPGF or on an oblique thrust fault associated with overthrusting of the Massif de la Selle. The results do support the conclusion that the 1770 earthquake was the last major earthquake in southern Haiti, with a magnitude upward of&nbsp;</span><strong>M</strong><span>&nbsp;7.5 and significantly more severe shaking in southern Haiti than during the 2010 earthquake.</span></p>","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120220108","usgsCitation":"Hough, S.E., Martin, S.S., Symithe, S., and Briggs, R.W., 2023, Rupture scenarios for the 3 June 1770 Haiti earthquake: Bulletin of the Seismological Society of America, v. 113, no. 1, p. 157-185, https://doi.org/10.1785/0120220108.","productDescription":"29 p.","startPage":"157","endPage":"185","ipdsId":"IP-142025","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":482159,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Haiti","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -71.67124675813444,\n              20.050612215978532\n            ],\n            [\n              -74.00169473999779,\n              19.905986033577463\n            ],\n            [\n              -74.57038450016687,\n              18.454888563255167\n            ],\n            [\n              -74.53298185535479,\n              17.77196094061692\n            ],\n            [\n              -71.6877773361758,\n              17.77196094061692\n            ],\n            [\n              -71.67124675813444,\n              20.050612215978532\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"113","issue":"1","noUsgsAuthors":false,"publicationDate":"2022-11-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Hough, Susan E. 0000-0002-5980-2986 hough@usgs.gov","orcid":"https://orcid.org/0000-0002-5980-2986","contributorId":587,"corporation":false,"usgs":true,"family":"Hough","given":"Susan","email":"hough@usgs.gov","middleInitial":"E.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":927626,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Martin, Stacey S.","contributorId":187758,"corporation":false,"usgs":false,"family":"Martin","given":"Stacey","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":927627,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Symithe, Steeve","contributorId":350978,"corporation":false,"usgs":false,"family":"Symithe","given":"Steeve","affiliations":[{"id":83892,"text":"Faculté Des Sciences, Université d'Etat d'Haïti, Port au Prince, Haïti","active":true,"usgs":false}],"preferred":false,"id":927628,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Briggs, Richard W. 0000-0001-8108-0046 rbriggs@usgs.gov","orcid":"https://orcid.org/0000-0001-8108-0046","contributorId":4136,"corporation":false,"usgs":true,"family":"Briggs","given":"Richard","email":"rbriggs@usgs.gov","middleInitial":"W.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":927629,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70239408,"text":"70239408 - 2023 - Life-cycle model reveals sensitive life stages and evaluates recovery options for a dwindling Pacific salmon population","interactions":[],"lastModifiedDate":"2023-03-01T17:09:22.001565","indexId":"70239408","displayToPublicDate":"2022-11-15T06:51:44","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"title":"Life-cycle model reveals sensitive life stages and evaluates recovery options for a dwindling Pacific salmon population","docAbstract":"<div id=\"article__content\" class=\"col-sm-12 col-md-8 col-lg-8 article__content article-row-left\"><div class=\"article__body \"><div class=\"abstract-group\"><div class=\"article-section__content en main\"><p>Population models, using empirical survival rates estimates for different life stages, can help managers explore whether various management options could stabilize a declining population or restore it to former levels of abundance. Here we used two decades of data on five life stages of the Cedar River, USA Sockeye Salmon,<span>&nbsp;</span><i>Oncorhynchus nerka</i>, population to create and parameterize a life-cycle model. This formerly large but unproductive population is now in steep decline, despite hatchery enhancement. We gathered population-specific data on survival during five stages: 1) egg-to-fry, 2) fry-to-presmolt, 3) presmolt-to-adult return from the ocean, 4) adult<span>&nbsp;</span><i>en route</i><span>&nbsp;</span>from the ocean to the spawning grounds, and 5) reproduction. We ground-truthed the model to ensure its fit to the data, and then we modified survival and other parameters during various stages to examine future scenarios. Our analyses revealed that low survival of juveniles in Lake Washington (stage 2: averaging only 3% over the last 20 years), survival of adults returning to fresh water to spawn (stage 4), and survival of adults on spawning grounds to reproduce (stage 5) are likely limiting factors. Combined increases in these stages and others (specifically, the proportion of fish taken into the hatchery to be spawned) might also recover the population. As in other integrated hatchery populations, managers must weigh options relating to balancing the fraction of natural- and hatchery-origin fish, and our results showed that increasing the fraction of fish taken into the hatchery alone will not recover the population. Our model brings together population-specific data to help managers weigh conservation strategies and understand which stages and habitats are most limiting and how much survival must increase to achieve recovery targets. By extension, our analyses also reveal the utility of such models in other cases where stage-specific data are available.</p></div></div></div></div>","language":"English","publisher":"American Fisheries Society","doi":"10.1002/nafm.10859","usgsCitation":"Kendall, N.W., Unrein, J.R., Volk, C., Beauchamp, D., Fresh, K.L., and Quinn, T.P., 2023, Life-cycle model reveals sensitive life stages and evaluates recovery options for a dwindling Pacific salmon population: North American Journal of Fisheries Management, v. 43, no. 1, p. 203-230, https://doi.org/10.1002/nafm.10859.","productDescription":"28 p.","startPage":"203","endPage":"230","ipdsId":"IP-137770","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":467133,"rank":2,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1002/nafm.10859","text":"External Repository"},{"id":411778,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"43","issue":"1","noUsgsAuthors":false,"publicationDate":"2022-11-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Kendall, Neala W.","contributorId":288624,"corporation":false,"usgs":false,"family":"Kendall","given":"Neala","email":"","middleInitial":"W.","affiliations":[{"id":61815,"text":"wafg","active":true,"usgs":false}],"preferred":false,"id":861483,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Unrein, Julia R.","contributorId":172777,"corporation":false,"usgs":false,"family":"Unrein","given":"Julia","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":861484,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Volk, Carol","contributorId":300802,"corporation":false,"usgs":false,"family":"Volk","given":"Carol","affiliations":[{"id":35354,"text":"Seattle Public Utilities","active":true,"usgs":false}],"preferred":false,"id":861485,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Beauchamp, David 0000-0002-3592-8381","orcid":"https://orcid.org/0000-0002-3592-8381","contributorId":217816,"corporation":false,"usgs":true,"family":"Beauchamp","given":"David","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":861486,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fresh, Kurt L.","contributorId":98597,"corporation":false,"usgs":false,"family":"Fresh","given":"Kurt","email":"","middleInitial":"L.","affiliations":[{"id":12448,"text":"U.S. National Oceanic and Atmospheric Administration","active":true,"usgs":false}],"preferred":false,"id":861487,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Quinn, Thomas P.","contributorId":167272,"corporation":false,"usgs":false,"family":"Quinn","given":"Thomas","email":"","middleInitial":"P.","affiliations":[{"id":24671,"text":"School of Aquatic and Fsiery Sciences, UW, Box 355020, Seattle, WA","active":true,"usgs":false}],"preferred":false,"id":861488,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
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