{"pageNumber":"148","pageRowStart":"3675","pageSize":"25","recordCount":40783,"records":[{"id":70237589,"text":"70237589 - 2022 - Defining the Hoek-Brown constant mi for volcanic lithologies","interactions":[],"lastModifiedDate":"2023-01-10T16:30:36.565423","indexId":"70237589","displayToPublicDate":"2022-12-05T11:49:27","publicationYear":"2022","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"displayTitle":"Defining the Hoek-Brown constant m<sub>i</sub> for volcanic lithologies","title":"Defining the Hoek-Brown constant mi for volcanic lithologies","docAbstract":"The empirical Hoek-Brown failure criterion is a well-known and commonly used failure criterion for both intact rocks and rock masses, especially in geological engineering. The intact criterion is calculated using experimental triaxial compression test results on intact samples while the rock mass criterion modifies the intact strength using quantified measures of the rock mass quality. The Hoek-Brown failure criterion includes a fitting constant for intact rocks, mi, which controls the steepness and curvature of the failure envelope, and is derived from curve-fitting the failure criterion to triaxial test data. However, because of the existence of tabulated mi values for various rock types, calculated using 1000’s of triaxial experiments, mi values are often extracted from the tables in the literature rather than the more time- and resource-intensive triaxial experiments. Using 100’s of triaxial experiments on variously altered volcanic rocks from volcanoes around the world, we demonstrate that mi varies dramatically based on a complex combination of alteration, lithology and texture, for example ranging from 2-38 for andesites. In contrast, tabulated estimates are typically given as small ranges, for example 25±5 for andesite. This means the failure criteria for volcanic rocks based on tabulated estimates could significantly over or under predict the intact strength, and thereby the rock mass strength, causing errors for stability and deformation assessments for a variety of volcanological and geological engineering purposes, from dome deformation or flank stability to excavation in volcanic rocks. In this research we not only highlight the high variability of mi for volcanic rocks, but by building on published relationships between porosity and strength, we demonstrate that it too is sensitive to porosity. We propose a number of preliminary methods to constrain mi values, including one using porosity.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Rock mechanics and engineering geology in volcanic fields","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"5th International Workshop on Rock Mechanics and Engineering Geology in Volcanic Fields","conferenceDate":"September 9-10, 2021","conferenceLocation":"Fukuoka, Japan","language":"English","publisher":"CRC Press","usgsCitation":"Villeneuve, M., Heap, M.J., and Schaefer, L.N., 2022, Defining the Hoek-Brown constant mi for volcanic lithologies, <i>in</i> Rock mechanics and engineering geology in volcanic fields, Fukuoka, Japan, September 9-10, 2021, p. 261-268.","productDescription":"8 p.","startPage":"261","endPage":"268","ipdsId":"IP-135372","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":411639,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":409800,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.taylorfrancis.com/books/edit/10.1201/9781003293590/rock-mechanics-engineering-geology-volcanic-fields-takehiro-ohta-takatoshi-ito-masahiko-osada","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Villeneuve, Marlène C.","contributorId":260116,"corporation":false,"usgs":false,"family":"Villeneuve","given":"Marlène C.","affiliations":[{"id":52510,"text":"Chair of Subsurface Engineering, Montanuniversität Leoben, Leoben, Austria","active":true,"usgs":false}],"preferred":false,"id":854543,"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":854544,"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":854545,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70263091,"text":"70263091 - 2022 - Drivers of habitat quality for a reintroduced elk herd","interactions":[],"lastModifiedDate":"2025-01-29T15:09:39.072874","indexId":"70263091","displayToPublicDate":"2022-12-05T00:00:00","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3358,"text":"Scientific Reports","active":true,"publicationSubtype":{"id":10}},"title":"Drivers of habitat quality for a reintroduced elk herd","docAbstract":"<p><span>Understanding spatiotemporal variation in habitat quality is essential for guiding wildlife reintroduction and restoration programs. The habitat productivity hypothesis posits that home range size is inversely related to habitat quality. Thus, home range size may be used as a proxy for habitat quality and can identify important land cover features for a recovering species. We sought to quantify variation in home range size across the biological cycle (seasons) for a reintroduced elk (</span><i>Cervus canadensis</i><span>) population in southwestern Virginia, USA and quantify habitat quality by linking home range sizes to the land cover types they contain using linear mixed-effects models. We found mean home range size was largest during late gestation for female elk. Additionally, throughout the year, smaller home ranges were associated with larger proportions of non-forested habitats whereas forested habitats were generally the opposite. However, both presumed poor- and high-quality habitats influenced female elk space use. Our approach revealed spatial variation in habitat quality for a recovering elk herd, demonstrated the importance of non-forested habitats to elk, can guide decisions regarding the location of future elk reintroduction programs, and serve as a model for evaluating habitat quality associated with wildlife reintroductions.</span></p>","language":"English","publisher":"Springer Nature","doi":"10.1038/s41598-022-25058-9","usgsCitation":"Quinlan, B., Rosenberger, J., Kalb, D., Abernathy, H., Thorne, E., Ford, W., and Cherry, M., 2022, Drivers of habitat quality for a reintroduced elk herd: Scientific Reports, v. 12, 20960, 12 p., https://doi.org/10.1038/s41598-022-25058-9.","productDescription":"20960, 12 p.","ipdsId":"IP-142591","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":489915,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-022-25058-9","text":"Publisher Index Page"},{"id":481447,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Virginia","otherGeospatial":"southwestern Virginia","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -82.81797132520401,\n              37.10392995435147\n            ],\n            [\n              -83.4791350332288,\n              36.59438261785931\n            ],\n            [\n              -80.45872432537026,\n              36.57458088905058\n            ],\n            [\n              -80.9768195014316,\n              37.315441708410084\n            ],\n            [\n              -81.71516471822216,\n              37.318178569421775\n            ],\n            [\n              -81.94847969969248,\n              37.58994839228791\n            ],\n            [\n              -82.81797132520401,\n              37.10392995435147\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"12","noUsgsAuthors":false,"publicationDate":"2022-12-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Quinlan, Braiden A.","contributorId":350149,"corporation":false,"usgs":false,"family":"Quinlan","given":"Braiden A.","affiliations":[{"id":25550,"text":"Virginia Polytechnic Institute and State University","active":true,"usgs":false}],"preferred":false,"id":925498,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rosenberger, Jacalyn P.","contributorId":350150,"corporation":false,"usgs":false,"family":"Rosenberger","given":"Jacalyn P.","affiliations":[{"id":56188,"text":"Virginia Department of Wildlife Resources","active":true,"usgs":false}],"preferred":false,"id":925499,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kalb, David M.","contributorId":350151,"corporation":false,"usgs":false,"family":"Kalb","given":"David M.","affiliations":[{"id":39552,"text":"Rhode Island Department of Environmental Management","active":true,"usgs":false}],"preferred":false,"id":925500,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Abernathy, Heather N.","contributorId":350220,"corporation":false,"usgs":false,"family":"Abernathy","given":"Heather N.","affiliations":[{"id":13724,"text":"Texas A&M University-Kingsville","active":true,"usgs":false}],"preferred":false,"id":925501,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Thorne, Emily D.","contributorId":350153,"corporation":false,"usgs":false,"family":"Thorne","given":"Emily D.","affiliations":[{"id":25550,"text":"Virginia Polytechnic Institute and State University","active":true,"usgs":false}],"preferred":false,"id":925502,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ford, W. Mark 0000-0002-9611-594X wford@usgs.gov","orcid":"https://orcid.org/0000-0002-9611-594X","contributorId":172499,"corporation":false,"usgs":true,"family":"Ford","given":"W. Mark","email":"wford@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":false,"id":925503,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Cherry, Michael J.","contributorId":350156,"corporation":false,"usgs":false,"family":"Cherry","given":"Michael J.","affiliations":[{"id":13724,"text":"Texas A&M University-Kingsville","active":true,"usgs":false}],"preferred":false,"id":925504,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70238881,"text":"70238881 - 2022 - Optimizing Landsat Next shortwave infrared bands for crop residue characterization","interactions":[],"lastModifiedDate":"2022-12-15T13:48:36.566374","indexId":"70238881","displayToPublicDate":"2022-12-03T07:44:55","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Optimizing Landsat Next shortwave infrared bands for crop residue characterization","docAbstract":"<p><span>This study focused on optimizing the placement of shortwave infrared (SWIR) bands for pixel-level estimation of fractional crop residue cover (</span><span class=\"html-italic\">f</span><sub>R</sub><span>) for the upcoming Landsat Next mission. We applied an iterative wavelength shift approach to a database of crop residue field spectra collected in Beltsville, Maryland, USA (n = 916) and computed generalized two- and three-band spectral indices for all wavelength combinations between 2000 and 2350 nm, then used these indices to model field-measured&nbsp;</span><span class=\"html-italic\">f</span><sub>R</sub><span>. A subset of the full dataset with a Normalized Difference Vegetation Index (NDVI) &lt; 0.3 threshold (n = 643) was generated to evaluate green vegetation impacts on&nbsp;</span><span class=\"html-italic\">f</span><sub>R</sub><span>&nbsp;estimation. For the two-band wavelength shift analyses applied to the NDVI &lt; 0.3 dataset, a generalized normalized difference using 2226 nm and 2263 nm bands produced the top&nbsp;</span><span class=\"html-italic\">f</span><sub>R</sub><span>&nbsp;estimation performance (</span><span class=\"html-italic\">R</span><sup>2</sup><span>&nbsp;= 0.8222;&nbsp;</span><span class=\"html-italic\">RMSE</span><span>&nbsp;= 0.1296). These findings were similar to the established two-band Shortwave Infrared Normalized Difference Residue Index (SINDRI) (</span><span class=\"html-italic\">R</span><sup>2</sup><span>&nbsp;= 0.8145;&nbsp;</span><span class=\"html-italic\">RMSE</span><span>&nbsp;= 0.1324). Performance of the two-band generalized normalized difference and SINDRI decreased for the full-NDVI dataset (</span><span class=\"html-italic\">R</span><sup>2</sup><span>&nbsp;= 0.5865 and 0.4144, respectively). For the three-band wavelength shift analyses applied to the NDVI &lt; 0.3 dataset, a generalized ratio-based index with a 2031–2085–2216 nm band combination, closely matching established Cellulose Absorption Index (CAI) bands, was top performing (</span><span class=\"html-italic\">R</span><sup>2</sup><span>&nbsp;= 0.8397;&nbsp;</span><span class=\"html-italic\">RMSE</span><span>&nbsp;= 0.1231). Three-band indices with CAI-type wavelengths maintained top&nbsp;</span><span class=\"html-italic\">f</span><sub>R</sub><span>&nbsp;estimation performance for the full-NDVI dataset with a 2036–2111–2217 nm band combination (</span><span class=\"html-italic\">R</span><sup>2</sup><span>&nbsp;= 0.7581;&nbsp;</span><span class=\"html-italic\">RMSE</span><span>&nbsp;= 0.1548). The 2036–2111–2217 nm band combination was also top performing in&nbsp;</span><span class=\"html-italic\">f</span><sub>R</sub><span>&nbsp;estimation (</span><span class=\"html-italic\">R</span><sup>2</sup><span>&nbsp;= 0.8690;&nbsp;</span><span class=\"html-italic\">RMSE</span><span>&nbsp;= 0.0970) for an additional analysis assessing combined green vegetation cover and surface moisture effects. Our results indicate that a three-band configuration with band centers and wavelength tolerances of 2036 nm (±5 nm), 2097 nm (±14 nm), and 2214 (±11 nm) would optimize Landsat Next SWIR bands for&nbsp;</span><span class=\"html-italic\">f</span><sub>R</sub><span>&nbsp;estimation.</span></p>","language":"English","publisher":"MDPI","doi":"10.3390/rs14236128","usgsCitation":"Lamb, B.T., Dennison, P., Hively, W.D., Kokaly, R.F., Serbin, G., Wu, Z., Dabney, P.W., Masek, J.G., Campbell, M., and Daughtry, C.S., 2022, Optimizing Landsat Next shortwave infrared bands for crop residue characterization: Remote Sensing, v. 14, no. 23, 6128, 29 p., https://doi.org/10.3390/rs14236128.","productDescription":"6128, 29 p.","ipdsId":"IP-144753","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":445721,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs14236128","text":"Publisher Index Page"},{"id":410537,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"14","issue":"23","noUsgsAuthors":false,"publicationDate":"2022-12-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Lamb, Brian T. 0000-0001-7957-5488","orcid":"https://orcid.org/0000-0001-7957-5488","contributorId":291893,"corporation":false,"usgs":true,"family":"Lamb","given":"Brian","middleInitial":"T.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":859052,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dennison, Phillip 0000-0002-0241-1917","orcid":"https://orcid.org/0000-0002-0241-1917","contributorId":266031,"corporation":false,"usgs":false,"family":"Dennison","given":"Phillip","email":"","affiliations":[{"id":54865,"text":"Dept. Geography, Utah State University","active":true,"usgs":false}],"preferred":false,"id":859053,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hively, W. Dean 0000-0002-5383-8064","orcid":"https://orcid.org/0000-0002-5383-8064","contributorId":201565,"corporation":false,"usgs":true,"family":"Hively","given":"W.","email":"","middleInitial":"Dean","affiliations":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":859054,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kokaly, Raymond F. 0000-0003-0276-7101","orcid":"https://orcid.org/0000-0003-0276-7101","contributorId":205165,"corporation":false,"usgs":true,"family":"Kokaly","given":"Raymond","email":"","middleInitial":"F.","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true},{"id":5078,"text":"Southwest Regional Director's Office","active":true,"usgs":true}],"preferred":true,"id":859055,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Serbin, Guy 0000-0001-9345-1772","orcid":"https://orcid.org/0000-0001-9345-1772","contributorId":266030,"corporation":false,"usgs":false,"family":"Serbin","given":"Guy","email":"","affiliations":[{"id":54864,"text":"EOAnalytics","active":true,"usgs":false}],"preferred":false,"id":859056,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wu, Zhuoting 0000-0001-7393-1832 zwu@usgs.gov","orcid":"https://orcid.org/0000-0001-7393-1832","contributorId":4953,"corporation":false,"usgs":true,"family":"Wu","given":"Zhuoting","email":"zwu@usgs.gov","affiliations":[{"id":498,"text":"Office of Land Remote Sensing (Geography)","active":true,"usgs":true},{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":859057,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Dabney, Philip W.","contributorId":214572,"corporation":false,"usgs":false,"family":"Dabney","given":"Philip","email":"","middleInitial":"W.","affiliations":[{"id":38788,"text":"NASA","active":true,"usgs":false}],"preferred":false,"id":859058,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Masek, Jeffery G.","contributorId":294418,"corporation":false,"usgs":false,"family":"Masek","given":"Jeffery","email":"","middleInitial":"G.","affiliations":[{"id":38788,"text":"NASA","active":true,"usgs":false}],"preferred":false,"id":859059,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Campbell, Michael","contributorId":299937,"corporation":false,"usgs":false,"family":"Campbell","given":"Michael","email":"","affiliations":[{"id":13252,"text":"University of Utah","active":true,"usgs":false}],"preferred":false,"id":859060,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Daughtry, Craig S. T.","contributorId":211093,"corporation":false,"usgs":false,"family":"Daughtry","given":"Craig","email":"","middleInitial":"S. T.","affiliations":[{"id":38179,"text":"USDA Agricultural Research Service, Hydrology and Remote Sensing Laboratory","active":true,"usgs":false}],"preferred":false,"id":859061,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70271307,"text":"70271307 - 2022 - Zinc on the edge—Isotopic and geophysical evidence that cratonic edges control world-class shale-hosted zinc-lead deposits","interactions":[],"lastModifiedDate":"2025-09-08T14:03:52.052483","indexId":"70271307","displayToPublicDate":"2022-12-03T00:00:00","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2746,"text":"Mineralium Deposita","active":true,"publicationSubtype":{"id":10}},"title":"Zinc on the edge—Isotopic and geophysical evidence that cratonic edges control world-class shale-hosted zinc-lead deposits","docAbstract":"<p><span>The North Australian Zinc Belt is the largest zinc-lead province in the world, containing three of the ten largest known individual deposits (HYC, Hilton-George Fisher, and Mount Isa). The Northern Cordillera in North America is the second largest zinc-lead province, containing a further two of the world’s top ten deposits (Red Dog and Howards Pass). Despite this world-class endowment, exploration in both mineral provinces during the past 2 decades has not been particularly successful, yielding only two significant discoveries (Teena, Australia, and Boundary, Canada). One of the most important aspects of exploration is to choose mineral provinces and districts within geological belts that have the greatest potential for discovery. Here, we present results from these two zinc belts that highlight previously unused datasets for area selection and targeting. Lead isotope mapping using analyses of mineralized material has identified gradients in μ (</span><sup>238</sup><span>U/</span><sup>204</sup><span>Pb) that coincide closely with many major deposits. Locations of these deposits also coincide with a gradient in the depth of the lithosphere-asthenosphere boundary determined from calibrated surface wave tomography models converted to temperature. Furthermore, gradients in upward-continued gravity anomalies and a step in Moho depth correspond to a pre-existing major crustal boundary in both zinc belts. A spatial association of deposits with a linear mid- to lower-crustal resistivity anomaly from magnetotelluric data is also observed in the North Australian Zinc Belt. The change from thicker to thinner lithosphere is interpreted to localize prospective basins for zinc-lead mineralization and to control the gradient in lead isotope and geophysical data. These data, when combined with data indicative of paleoenvironment and changes in plate motion at the time of mineralization, provide new exploration criteria that can be used to identify prospective mineralized basins and define the most favorable parts of these basins.</span></p>","language":"English","publisher":"Springer Nature","doi":"10.1007/s00126-022-01153-9","usgsCitation":"Huston, D.L., Champion, D.C., Czarnota, K., Duan, J., Hutchens, M., Paradis, S., Hoggard, M., Ware, B., Gibson, G.M., Doublier, M.P., Kelley, K.D., McCafferty, A.E., Hayward, N., Richards, F., Tessalina, S., and Carr, G., 2022, Zinc on the edge—Isotopic and geophysical evidence that cratonic edges control world-class shale-hosted zinc-lead deposits: Mineralium Deposita, v. 58, p. 707-729, https://doi.org/10.1007/s00126-022-01153-9.","productDescription":"23  p.","startPage":"707","endPage":"729","ipdsId":"IP-135613","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":495149,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":495180,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s00126-022-01153-9","text":"Publisher Index Page"}],"country":"Australia","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              134.27421209840645,\n              -14.569058942329349\n            ],\n            [\n              134.27421209840645,\n              -25.53495369611406\n            ],\n            [\n              142.46091725232395,\n              -25.53495369611406\n            ],\n            [\n              142.46091725232395,\n              -14.569058942329349\n            ],\n            [\n              134.27421209840645,\n              -14.569058942329349\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"58","noUsgsAuthors":false,"publicationDate":"2022-12-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Huston, David L. 0000-0002-1740-6336","orcid":"https://orcid.org/0000-0002-1740-6336","contributorId":328600,"corporation":false,"usgs":false,"family":"Huston","given":"David","middleInitial":"L.","affiliations":[{"id":35920,"text":"Geoscience Australia","active":true,"usgs":false}],"preferred":false,"id":947910,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Champion, David C.","contributorId":360913,"corporation":false,"usgs":false,"family":"Champion","given":"David","middleInitial":"C.","affiliations":[],"preferred":false,"id":947911,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Czarnota, 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,{"id":70238684,"text":"70238684 - 2022 - Can we avert an Amazon tipping point? The economic and environmental costs","interactions":[],"lastModifiedDate":"2022-12-05T12:37:03.967845","indexId":"70238684","displayToPublicDate":"2022-12-02T06:32:43","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1562,"text":"Environmental Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Can we avert an Amazon tipping point? The economic and environmental costs","docAbstract":"<div class=\"article-text wd-jnl-art-abstract cf\"><p>The Amazon biome is being pushed by unsustainable economic drivers towards an ecological tipping point where restoration to its previous state may no longer be possible. This degradation is the result of self-reinforcing interactions between deforestation, climate change and fire. We assess the economic, natural capital and ecosystem services impacts and trade-offs of scenarios representing movement towards an Amazon tipping point and strategies to avert one using the Integrated Economic-Environmental Modeling (IEEM) Platform linked with spatial land use-land cover change and ecosystem services modeling (IEEM + ESM). Our approach provides the first approximation of the economic, natural capital and ecosystem services impacts of a tipping point, and evidence to build the economic case for strategies to avert it. For the five Amazon focal countries, namely, Brazil, Peru, Colombia, Bolivia and Ecuador, we find that a tipping point would create economic losses of US$256.6 billion in cumulative gross domestic product by 2050. Policies that would contribute to averting a tipping point, including strongly reducing deforestation, investing in intensifying agriculture in cleared lands, climate-adapted agriculture and improving fire management, would generate approximately US$339.3 billion in additional wealth and a return on investment of US$29.5 billion. Quantifying the costs, benefits and trade-offs of policies to avert a tipping point in a transparent and replicable manner can support the design of regional development strategies for the Amazon biome, build the business case for action and catalyze global cooperation and financing to enable policy implementation.</p></div>","language":"English","publisher":"IOP Publishing","doi":"10.1088/1748-9326/aca3b8","usgsCitation":"Banerjee, O., Cicowiez, M., Macedo, M., Malek, Z., Verburg, P.H., Goodwin, S., Vargas, R., Rattis, L., Bagstad, K.J., Brando, P.M., Coe, M.T., Neill, C., Damiani Marti, O., and Avila Murillo, J., 2022, Can we avert an Amazon tipping point? 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,{"id":70244199,"text":"70244199 - 2022 - Appendix 7: Application of joint dynamic species distribution models to at-sea survey data for seabirds in the Bering Strait and Chukchi Sea","interactions":[],"lastModifiedDate":"2024-03-29T16:01:06.647503","indexId":"70244199","displayToPublicDate":"2022-12-01T10:51:28","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesNumber":"BOEM 2022-067","title":"Appendix 7: Application of joint dynamic species distribution models to at-sea survey data for seabirds in the Bering Strait and Chukchi Sea","docAbstract":"<p>Mitigating risk to migratory birds from energy development requires information on the distribution and abundance of seabirds in offshore waters. Seabirds are highly mobile, with species-specific seasonal migrations that result in variable patterns of distribution in space and time. In remote offshore marine areas, obtaining useful and current information on resources is difficult to achieve and maintain, both fiscally and logistically, necessitating collaborative effort (Danielson et al. 2022). We used seabird at-sea survey data (2007-2021) and new modeling techniques to develop spatio-temporal models of seasonal abundance and distribution of species in waters of the Pacific Arctic. For six species groups selected as model test cases, we identified fine-scale distributions for each year, using data collected during summer to early fall (June through September). Our approach uses the best available data and can be updated as new data are generated, providing up-to-date information for regions with existing or potential future oil and gas development.</p>","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Marine bird distribution and abundance in offshore waters","largerWorkSubtype":{"id":1,"text":"Federal Government Series"},"language":"English","publisher":"Bureau of Ocean Energy Management (BOEM AK-17-03)","usgsCitation":"Arimitsu, M.L., and Kathy Kuletz, 2022, Appendix 7: Application of joint dynamic species distribution models to at-sea survey data for seabirds in the Bering Strait and Chukchi Sea, 13 p.","productDescription":"13 p.","startPage":"163","endPage":"175","ipdsId":"IP-144357","costCenters":[{"id":65299,"text":"Alaska Science Center Ecosystems","active":true,"usgs":true}],"links":[{"id":417892,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.boem.gov/regions/alaska-ocs-region/scientific-and-technical-publications-2022"},{"id":427246,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Russia, United States","otherGeospatial":"Beaufort Sea, Bering Sea, Chukchi Sea","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -179.9,\n              72\n            ],\n            [\n              -179.9,\n              62\n            ],\n            [\n              -146,\n              62\n            ],\n            [\n              -146,\n              72\n            ],\n            [\n              -179.9,\n              72\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Arimitsu, Mayumi L. 0000-0001-6982-2238 marimitsu@usgs.gov","orcid":"https://orcid.org/0000-0001-6982-2238","contributorId":140501,"corporation":false,"usgs":true,"family":"Arimitsu","given":"Mayumi","email":"marimitsu@usgs.gov","middleInitial":"L.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":874854,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kathy Kuletz","contributorId":306145,"corporation":false,"usgs":false,"family":"Kathy Kuletz","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":874855,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70242775,"text":"70242775 - 2022 - Supplemental vegetation monitoring plots at Little Bighorn Battlefield National Monument to accelerate learning of the Annual Brome Adaptive Management (ABAM) model","interactions":[],"lastModifiedDate":"2024-03-05T16:34:42.657934","indexId":"70242775","displayToPublicDate":"2022-12-01T10:29:26","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"seriesTitle":{"id":7577,"text":"Annual Report","active":true,"publicationSubtype":{"id":4}},"title":"Supplemental vegetation monitoring plots at Little Bighorn Battlefield National Monument to accelerate learning of the Annual Brome Adaptive Management (ABAM) model","docAbstract":"The Annual Brome Adaptive Management (ABAM) project is a consortium of seven parks in the Northern Great Plains (NGP) working together to better understand how to control invasive annual grasses (including Bromus species) through an adaptive management approach. 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,{"id":70242768,"text":"70242768 - 2022 - Fort Laramie National Historic Site 2022 ABAM Investigator Annual Report","interactions":[],"lastModifiedDate":"2024-03-05T16:22:08.807736","indexId":"70242768","displayToPublicDate":"2022-12-01T10:13:24","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"seriesTitle":{"id":7577,"text":"Annual Report","active":true,"publicationSubtype":{"id":4}},"title":"Fort Laramie National Historic Site 2022 ABAM Investigator Annual Report","docAbstract":"<p>The Annual Brome Adaptive Management (ABAM) project is a consortium of seven parks in the Northern Great Plains working together to better understand how to control invasive annual grasses (including <i>Bromus</i> species) through an adaptive management approach. This approach is supported by a quantitative model that uses current data from standardized vegetation monitoring plots in all seven parks to annually update the model's parameters and predictions regarding the effects of different management actions on invasive annual grasses and other components of the mixed-grass prairie plant community. This updating is called \"learning.\" Currently, the ABAM model has little information about the effects of the herbicide indaziflam, applied alone or together with the herbicide imazapic, at different times during the growing season, on target invasive annual grasses and other components of the vegetation. The purpose of this study is to increase the amount of information about this herbicide and therefore accelerate the rate of learning accomplished in the adaptive management cycle.</p>","language":"English","publisher":"National Park Service","usgsCitation":"Symstad, A., 2022, Fort Laramie National Historic Site 2022 ABAM Investigator Annual Report: Annual Report, 3 p.","productDescription":"3 p.","ipdsId":"IP-152071","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":415836,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://irma.nps.gov/RPRS/IAR/Profile/573318","linkFileType":{"id":5,"text":"html"}},{"id":426324,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","otherGeospatial":"Fort Laramie National Historic Site","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -104.56770704017384,\n              42.210821091328\n            ],\n            [\n              -104.56770704017384,\n              42.19287280305102\n            ],\n            [\n              -104.52383325080481,\n              42.19287280305102\n            ],\n            [\n              -104.52383325080481,\n              42.210821091328\n            ],\n            [\n              -104.56770704017384,\n              42.210821091328\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Symstad, Amy 0000-0003-4231-2873 asymstad@usgs.gov","orcid":"https://orcid.org/0000-0003-4231-2873","contributorId":201095,"corporation":false,"usgs":true,"family":"Symstad","given":"Amy","email":"asymstad@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":869741,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70242767,"text":"70242767 - 2022 - Supplemental vegetation monitoring plots at Wind Cave National Park to accelerate learning of the Annual Brome Adaptive Management (ABAM) model","interactions":[],"lastModifiedDate":"2024-03-05T16:41:17.236689","indexId":"70242767","displayToPublicDate":"2022-12-01T09:55:41","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"seriesTitle":{"id":7577,"text":"Annual Report","active":true,"publicationSubtype":{"id":4}},"title":"Supplemental vegetation monitoring plots at Wind Cave National Park to accelerate learning of the Annual Brome Adaptive Management (ABAM) model","docAbstract":"<p>The Annual Brome Adaptive Management (ABAM) project is a consortium of seven parks in the Northern Great Plains (NGP) working together to better understand how to control invasive annual grasses (including <i>Bromus</i> species) through an adaptive management approach. This approach is supported by a quantitative model that uses current data from standardized vegetation monitoring plots in all seven parks to annually update the model’s parameters and predictions regarding the effects of different management actions on invasive annual grasses and other components of the mixed-grass prairie plant community. This updating of the model is called “learning.”</p><p>The ABAM model includes treatments in which the herbicides indaziflam and imazapic are applied alone or in combination with or without a prescribed fire preceding or following their application. However, the original ABAM model did not have field data for the effects of those treatments on target invasive annual grasses and other components of the vegetation in conditions like those that frequently occur in ABAM parks (i.e., ungrazed). The purpose of this study is to increase the amount of information about these treatments and therefore accelerate the rate of learning accomplished in the adaptive management cycle.</p>","language":"English","publisher":"National Park Service","usgsCitation":"Symstad, A., and Richardson, T., 2022, Supplemental vegetation monitoring plots at Wind Cave National Park to accelerate learning of the Annual Brome Adaptive Management (ABAM) model: Annual Report, 4 p.","productDescription":"4 p.","ipdsId":"IP-152075","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":415835,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://irma.nps.gov/RPRS/IAR/Profile/573317","linkFileType":{"id":5,"text":"html"}},{"id":426321,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"South Dakota","otherGeospatial":"Wind Cave National Park","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -103.49938816977327,\n              43.633694711675986\n            ],\n            [\n              -103.5024470931983,\n              43.55944982284214\n            ],\n            [\n              -103.52141241843475,\n              43.54383294926339\n            ],\n            [\n              -103.52202420312013,\n              43.52023368800823\n            ],\n            [\n              -103.45748091884613,\n              43.51534889803226\n            ],\n            [\n              -103.45657280095472,\n              43.53372182682589\n            ],\n            [\n              -103.43975828125109,\n              43.5356829718161\n            ],\n            [\n              -103.44038918420713,\n              43.58528414983906\n            ],\n            [\n              -103.41717960271762,\n              43.58473704935065\n            ],\n            [\n              -103.41664429111844,\n              43.56545928494155\n            ],\n            [\n              -103.38062546778514,\n              43.56346760240271\n            ],\n            [\n              -103.38009015618593,\n              43.56812536845743\n            ],\n            [\n              -103.36058951934952,\n              43.56694573600919\n            ],\n            [\n              -103.3588306383801,\n              43.592360590123576\n            ],\n            [\n              -103.34185361336944,\n              43.59180514516018\n            ],\n            [\n              -103.33680638971731,\n              43.60876454212675\n            ],\n            [\n              -103.33665344354603,\n              43.62660987781496\n            ],\n            [\n              -103.3485832449052,\n              43.62505981511873\n            ],\n            [\n              -103.35317163004311,\n              43.63059510828057\n            ],\n            [\n              -103.43729202423958,\n              43.63170210623065\n            ],\n            [\n              -103.45365726456492,\n              43.640225573499706\n            ],\n            [\n              -103.48019342527975,\n              43.641830445497\n            ],\n            [\n              -103.49938816977327,\n              43.633694711675986\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Symstad, Amy 0000-0003-4231-2873 asymstad@usgs.gov","orcid":"https://orcid.org/0000-0003-4231-2873","contributorId":201095,"corporation":false,"usgs":true,"family":"Symstad","given":"Amy","email":"asymstad@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":869740,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Richardson, Timm","contributorId":334581,"corporation":false,"usgs":false,"family":"Richardson","given":"Timm","email":"","affiliations":[],"preferred":false,"id":895967,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70238720,"text":"70238720 - 2022 - PHREEQ-N-AMDTreat+REYs water-quality modeling tools to evaluate acid mine drainage treatment strategies for recovery of rare-earth elements","interactions":[],"lastModifiedDate":"2024-02-23T16:04:23.105819","indexId":"70238720","displayToPublicDate":"2022-12-01T09:55:30","publicationYear":"2022","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"PHREEQ-N-AMDTreat+REYs water-quality modeling tools to evaluate acid mine drainage treatment strategies for recovery of rare-earth elements","docAbstract":"<p>The PHREEQ-N-AMDTreat+REYs water-quality modeling tools have the fundamental capability to simulate aqueous chemical reactions and predict the formation of metal-rich solids during the treatment of acid mine drainage (AMD). These new user-friendly, publicly available&nbsp;tools were expanded from the PHREEQ-N-AMDTreat tools to include the precipitation of rare-earth elements plus yttrium (REYs) and the adsorption of REYs onto hydrous Fe, Al, and Mn&nbsp;oxides. The tool set consists of a caustic titration model that indicates equilibrium surface and aqueous speciation of REYs as functions of pH and caustic agent, and a kinetics+adsorption model that simulates progressive changes in pH, major ions, and REYs in water and solids during sequential steps through passive and/or active treatment. Each model has a user interface (UI) that facilitates the input of water-quality data and adjustment to geochemical or treatment system variables; for example, retention time and aeration rate are adjustable parameters in the kinetics model. On-screen graphs display results of changes in metals and associated solute concentrations as functions of pH or retention time; details are summarized in output tables. A goal of such modeling is to identify strategies that could produce a concentrated REYs extract from AMD or mine waste leachate. For example, if REYs could be concentrated after first removing substantial Fe and Al, the final REYs-bearing phase(s) could be more efficiently processed for REYs recovery and, therefore, may represent a more valuable commodity. Preliminary modeling supports the hypothesis that Fe and Al can be removed at pH &lt; 5.5 using conventional sequential oxidation and neutralization treatment processes without removing REYs, and that further increasing pH can promote the adsorption of REYs by hydrous Mn oxides. Alternatively, chemicals such as oxalate or phosphate may be added to precipitate REYs compounds following initial steps to decrease Fe and Al concentrations. The aqueous geochemical model framework is comprehensive and permits evaluation of effects from interactive chemical and physical variables. Field studies that demonstrate REYs attenuation from AMD and corresponding solid-phase formation during specific treatment steps plus laboratory studies of aqueous/solid interactions are helpful to corroborate, refine, and constrain modelin parameters.</p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of the 12th International Conference on Acid Mine Drainage","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"12th International Conference on Acid Mine Drainage","conferenceDate":"September 18-24, 2022","language":"English","publisher":"University of Queensland","usgsCitation":"Cravotta, C., 2022, PHREEQ-N-AMDTreat+REYs water-quality modeling tools to evaluate acid mine drainage treatment strategies for recovery of rare-earth elements, <i>in</i> Proceedings of the 12th International Conference on Acid Mine Drainage, September 18-24, 2022, p. 788-804.","productDescription":"7 p.","startPage":"788","endPage":"804","ipdsId":"IP-137202","costCenters":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"links":[{"id":410097,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://smi.uq.edu.au/conferences/international-conference-acid-rock-drainage-2022","linkFileType":{"id":5,"text":"html"}},{"id":425945,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Cravotta, Charles A. III 0000-0003-3116-4684","orcid":"https://orcid.org/0000-0003-3116-4684","contributorId":207249,"corporation":false,"usgs":true,"family":"Cravotta","given":"Charles A.","suffix":"III","affiliations":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"preferred":true,"id":858359,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70263323,"text":"70263323 - 2022 - Understory structure and heterospecifics influence the occupancy of a ground-nesting species of conservation concern, the Canada Warbler","interactions":[],"lastModifiedDate":"2025-02-06T16:00:27.11247","indexId":"70263323","displayToPublicDate":"2022-12-01T09:54:10","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":947,"text":"Avian Conservation and Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Understory structure and heterospecifics influence the occupancy of a ground-nesting species of conservation concern, the Canada Warbler","docAbstract":"<p><span>Forest structure and composition in eastern U.S. forests are changing because of forest regeneration after farmland abandonment, less frequent occurrence of severe disturbances, and climate change. Some of these changes may disproportionally affect birds that rely on gap dynamics or other forest canopy disturbances to create understory habitat. The Canada Warbler (</span><i>Cardellina canadensis</i><span>) is one such understory specialist that has undergone consistent declines. We assessed environmental and interspecific factors associated with Canada Warbler space use in its southern breeding distribution to understand potential causes of population declines and inform conservation efforts. We evaluated Canada Warbler occupancy from 840 point count surveys conducted in 2017 and 2018 at 470 unique locations (79% of locations surveyed in both years) throughout Monongahela National Forest, West Virginia, USA. We modeled Canada Warbler occupancy probability as a function of environmental variables and included Black-throated Blue Warbler (</span><i>Setophaga caerulescens</i><span>) and Hermit Thrush (</span><i>Catharus guttatus</i><span>) as interacting species because all three species exhibit similar habitat preferences. Canada Warblers were most likely to occur in areas with rhododendron (</span><i>Rhododendron maximum</i><span>) density &gt; 0.27 stems/m² and within 3 m of riparian areas (streams and wetlands). They were also more likely to occur in mid-elevation (highest occupancy at 930 m) northern hardwood forests when Black-throated Blue Warblers were also present. Black-throated Blue Warblers were most likely to occupy mid-elevation sites with high shrub density, whereas Hermit Thrushes were more likely to occupy high-elevation, old-age forests. Potential management actions could focus on conserving riparian areas in northern hardwood forests, especially those with dense rhododendron thickets. Such potential actions could also be beneficial across the entire elevation range we explored within the region (500–1300 m). Canada Warblers may be benefiting from the recent spread of rhododendron habitats and northern hardwood forest types within West Virginia.</span></p>","language":"English","publisher":"Resilience Alliance Publications","doi":"10.5751/ace-02079-170120","usgsCitation":"Dimmig, G., Rota, C., Wood, P.B., and Lituma, C., 2022, Understory structure and heterospecifics influence the occupancy of a ground-nesting species of conservation concern, the Canada Warbler: Avian Conservation and Ecology, v. 17, no. 1, 20, 16 p., https://doi.org/10.5751/ace-02079-170120.","productDescription":"20, 16 p.","ipdsId":"IP-123270","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":487031,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5751/ace-02079-170120","text":"Publisher Index Page"},{"id":481747,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United sTates","state":"West Virginia","otherGeospatial":"Monongahela National Forest","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -80.58889045378262,\n              37.463537077379684\n            ],\n            [\n              -80.3485425975682,\n              37.51121532612136\n            ],\n            [\n              -79.62749902892529,\n              38.552413228981266\n            ],\n            [\n              -79.33707870266615,\n              38.442685588318085\n            ],\n            [\n              -78.8463684962287,\n              39.0674460432719\n            ],\n            [\n              -79.48729611280025,\n              39.1995023289459\n            ],\n            [\n              -79.48729611280025,\n              39.455139390658985\n            ],\n            [\n              -79.8978903671664,\n              39.37777230668391\n            ],\n            [\n              -81.23983256436323,\n              37.88364086385796\n            ],\n            [\n              -81.01951369616684,\n              37.54298391685913\n            ],\n            [\n              -80.58889045378262,\n              37.463537077379684\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"17","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Dimmig, Gordon W.","contributorId":350556,"corporation":false,"usgs":false,"family":"Dimmig","given":"Gordon W.","affiliations":[{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":926339,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rota, Christopher T.","contributorId":350557,"corporation":false,"usgs":false,"family":"Rota","given":"Christopher T.","affiliations":[{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":926340,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wood, Petra B. 0000-0002-8575-1705 pbwood@usgs.gov","orcid":"https://orcid.org/0000-0002-8575-1705","contributorId":199090,"corporation":false,"usgs":true,"family":"Wood","given":"Petra","email":"pbwood@usgs.gov","middleInitial":"B.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":926338,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lituma, Christopher M.","contributorId":350558,"corporation":false,"usgs":false,"family":"Lituma","given":"Christopher M.","affiliations":[{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":926341,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70238719,"text":"70238719 - 2022 - Determination and prediction of rare earth element eeochemical associations in acid mine drainage treatment wastes","interactions":[],"lastModifiedDate":"2024-02-23T15:37:15.333066","indexId":"70238719","displayToPublicDate":"2022-12-01T09:36:32","publicationYear":"2022","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Determination and prediction of rare earth element eeochemical associations in acid mine drainage treatment wastes","docAbstract":"<p>Acid mine drainage (AMD) has been proposed by various researchers as a novel source of rare earth elements (REE), a group of elements that include critical metals for clean energy and modern technologies. REE tend to be sequestered in the Fe-Al-Mn-rich solids produced during the treatment of AMD. These solids are typically managed as waste, but could be a low-cost, readily available REE source. Here, results from field sampling, solids characterization, and geochemical modeling are presented to identify the mechanism(s) of REE attenuation and determine the minerals/solid phases in AMD solids that are enriched in REE. </p><p>This study reveals that solids produced from low-pH AMD that was passively treated by limestone contain elevated concentrations of REE with Al, Fe, and/or Mn. AMD solid characterization via sequential extraction demonstrated that Al and Mn oxides were more abundant than Fe oxides and that the REEs are mainly associated with Al/Mn phases. Additionally, sequential extractions demonstrate that for the AMD solids evaluated, acidic and/or reducing extractions are required to mobilize the REE. Finally, the “CausticTitrationREYs.exe” geochemical equilibrium model demonstrated in this study indicates that the observed dissolved REE attenuation can be explained via surface complexation on Fe, Al, and Mn oxides/hydroxides and not by REE compound precipitation. The model accurately predicts the pH dependent removal of dissolved REE and that Al and Mn oxides/hydroxides are largely responsible for dissolved REE removal for the systems evaluated. The modeling results are consistent with the characterization results that show that Al and Mn hydroxides are important hosting phases of REEs in AMD treatment systems. </p><p>The results presented here can be used to identify conditions favorable for accumulation of REE-enriched AMD solids and possible chemical treatment(s) to mobilize REE. The geochemical model can be applied to active and/or passive AMD treatment systems to predict REE attenuation with Fe, Al, and Mn during treatment and what phases may be enriched in REE. This information can be used to engineer AMD systems to produce specific phases enriched in REE. The recovery of REE from AMD solids is an opportunity to transform the environmental and economical challenge of polluted mine drainage into an asset.</p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of the 12th International Conference on Acid Rock Drainage","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"12th International Conference on Acid Rock Drainage","conferenceDate":"September 18-24, 2022","language":"English","publisher":"University of Queensland","usgsCitation":"Hedin, B., Cravotta, C., Stuckman, M., Lopano, C., Capo, R., and Hedin, R., 2022, Determination and prediction of rare earth element eeochemical associations in acid mine drainage treatment wastes, <i>in</i> Proceedings of the 12th International Conference on Acid Rock Drainage, September 18-24, 2022, p. 626-633.","productDescription":"8 p.","startPage":"626","endPage":"633","ipdsId":"IP-141129","costCenters":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"links":[{"id":425944,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":410096,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://smi.uq.edu.au/conferences/international-conference-acid-rock-drainage-2022"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hedin, B.C.","contributorId":299679,"corporation":false,"usgs":false,"family":"Hedin","given":"B.C.","email":"","affiliations":[{"id":64931,"text":"Hedin Environmental Inc.","active":true,"usgs":false}],"preferred":false,"id":858353,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cravotta, Charles A. III 0000-0003-3116-4684","orcid":"https://orcid.org/0000-0003-3116-4684","contributorId":207249,"corporation":false,"usgs":true,"family":"Cravotta","given":"Charles A.","suffix":"III","affiliations":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"preferred":true,"id":858354,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stuckman, M.Y.","contributorId":299680,"corporation":false,"usgs":false,"family":"Stuckman","given":"M.Y.","affiliations":[{"id":64933,"text":"National Energy Technology Laboratory","active":true,"usgs":false}],"preferred":false,"id":858355,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lopano, C.L.","contributorId":299681,"corporation":false,"usgs":false,"family":"Lopano","given":"C.L.","affiliations":[{"id":64933,"text":"National Energy Technology Laboratory","active":true,"usgs":false}],"preferred":false,"id":858356,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Capo, R.C.","contributorId":299682,"corporation":false,"usgs":false,"family":"Capo","given":"R.C.","affiliations":[{"id":12465,"text":"University of Pittsburgh","active":true,"usgs":false}],"preferred":false,"id":858357,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hedin, R.S.","contributorId":299683,"corporation":false,"usgs":false,"family":"Hedin","given":"R.S.","email":"","affiliations":[{"id":64931,"text":"Hedin Environmental Inc.","active":true,"usgs":false}],"preferred":false,"id":858358,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70230030,"text":"70230030 - 2022 - Geologic setting and geomorphic history of La Botica and surrounding area","interactions":[],"lastModifiedDate":"2026-03-18T14:06:14.010431","indexId":"70230030","displayToPublicDate":"2022-12-01T08:54:09","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":3,"text":"Organization Series"},"seriesTitle":{"id":23617,"text":"Research Contributions","active":true,"publicationSubtype":{"id":3}},"seriesNumber":"115","title":"Geologic setting and geomorphic history of La Botica and surrounding area","docAbstract":"<p>La Botica is located on the gently east-dipping marginal area between the high San Juan Mountains to the west and the San Luis Basin to the east in south-central Colorado. The site is positioned on a topographic bench perched about 70 to 80 m above La Jara Creek (figure 2.1), a tributary to the Rio Grande. The unique floral assemblage at La Botica has resulted in intermittent occupation over the last several thousand years. The physical environment supporting this assemblage is a result of Quaternary surface processes that have modified the underlying Tertiary bedrock. Underlying bedrock at the site consists of Oligocene to Pliocene volcanic and sedimentary deposits related to the Rio Grande rift and the San Juan volcanic locus of the Southern Rocky Mountains volcanic field. Local bedrock is mildly deformed by normal faulting and eastward tilting due to the onset of Oligocene extensional deformation and initial formation of the San Luis Basin. The geomorphic evolution and incision history of La Jara Creek are directly linked to middle to late Pleistocene evolution of the Rio Grande and to regional alpine glacial cycles over the last 500 k.y. (thousand years). Subsequent degradation of surrounding bedrock and development of mass-wasting deposits, such as landslides and talus slopes, have strongly influenced the incision history of La Jara Creek and the local environment at La Botica. In addition, local talus slopes and blockfields can host processes that actively modify the local environment, and these processes may have contributed to establishment of the floral assemblage.</p>","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Multidisciplinary research at the La Botica site, Conjeos County, Colorado","largerWorkSubtype":{"id":3,"text":"Organization Series"},"language":"English","publisher":"Paleocultural Research Group","usgsCitation":"Turner, K.J., Ruleman, C.A., and Mahan, S.A., 2022, Geologic setting and geomorphic history of La Botica and surrounding area: Research Contributions 115, 20 p.","productDescription":"20 p.","startPage":"9","endPage":"28","ipdsId":"IP-123501","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":501237,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":501236,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://paleocultural.org/Research/la-botica/"}],"country":"United States","state":"Colorado","otherGeospatial":"La Botica","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -106.79256393659836,\n              37.70573798045494\n            ],\n            [\n              -106.79256393659836,\n              37.02301823232551\n            ],\n            [\n              -105.74755024473933,\n              37.02301823232551\n            ],\n            [\n              -105.74755024473933,\n              37.70573798045494\n            ],\n            [\n              -106.79256393659836,\n              37.70573798045494\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Turner, Kenzie J. 0000-0002-4940-3981 kturner@usgs.gov","orcid":"https://orcid.org/0000-0002-4940-3981","contributorId":496,"corporation":false,"usgs":true,"family":"Turner","given":"Kenzie","email":"kturner@usgs.gov","middleInitial":"J.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":838788,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ruleman, Chester A. 0000-0002-1503-4591 cruleman@usgs.gov","orcid":"https://orcid.org/0000-0002-1503-4591","contributorId":1264,"corporation":false,"usgs":true,"family":"Ruleman","given":"Chester","email":"cruleman@usgs.gov","middleInitial":"A.","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":838789,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mahan, Shannon A. 0000-0001-5214-7774 smahan@usgs.gov","orcid":"https://orcid.org/0000-0001-5214-7774","contributorId":147159,"corporation":false,"usgs":true,"family":"Mahan","given":"Shannon","email":"smahan@usgs.gov","middleInitial":"A.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":838790,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70242763,"text":"70242763 - 2022 - Supplemental vegetation monitoring plots at Badlands National Park to accelerate learning of the Annual Brome Adaptive Management (ABAM) model","interactions":[],"lastModifiedDate":"2024-03-05T15:12:59.931116","indexId":"70242763","displayToPublicDate":"2022-12-01T08:53:45","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"seriesTitle":{"id":7577,"text":"Annual Report","active":true,"publicationSubtype":{"id":4}},"title":"Supplemental vegetation monitoring plots at Badlands National Park to accelerate learning of the Annual Brome Adaptive Management (ABAM) model","docAbstract":"The annual Brome Adaptive Management (ABAM) project is a consortium of seven parks in the Northern Great Plains working together to better understand how to control invasive annual grasses (including Bromus species) through an adaptive management approach. This approach is supported by a quantitative model that uses current data from standardized vegetation monitoring plots in all seven parks to annually update the model’s parameters and predictions regarding the effects of different management actions on invasive annual grasses and other components of the mixed-grass prairie plant community. This updating of the model is called “learning.” The ABAM model includes treatments in which the herbicides indaziflam and imazapic are applied alone or in combination with or without a prescribed fire preceding or following their application. However, the ABAM model currently does not have field data for the effects of those treatments on target invasive annual grasses and other components of the vegetation in conditions like those that frequently occur in ABAM parks. This annual report provides raw results of these treatments applied to plots at Badlands National Park established specifically to accumulate this type of data and therefore accelerate the rate of learning accomplished in the adaptive management cycle.","language":"English","publisher":"National Park Service","usgsCitation":"Symstad, A., 2022, Supplemental vegetation monitoring plots at Badlands National Park to accelerate learning of the Annual Brome Adaptive Management (ABAM) model: Annual Report, 4 p.","productDescription":"4 p.","ipdsId":"IP-152066","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":415833,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://irma.nps.gov/RPRS/IAR/Profile/573319"},{"id":426319,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"South Dakota","otherGeospatial":"Badlands National 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asymstad@usgs.gov","orcid":"https://orcid.org/0000-0003-4231-2873","contributorId":201095,"corporation":false,"usgs":true,"family":"Symstad","given":"Amy","email":"asymstad@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":869738,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70239795,"text":"70239795 - 2022 - Osmoregulation and acid-base balance.","interactions":[],"lastModifiedDate":"2023-01-20T14:50:53.947059","indexId":"70239795","displayToPublicDate":"2022-12-01T08:49:30","publicationYear":"2022","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"9","title":"Osmoregulation and acid-base balance.","docAbstract":"<p>Maintaining relatively constant levels of internal cellular ions is critical to the normal function of all animals. For many organisms this is achieved primarily by regulating the ion and acid-base composition of the blood within narrow limits. This understanding of the importance of “le milieu interior,” first espoused by Claude Bernard in the mid-1800s and later described as “homeostasis” by Walter Cannon, is a cornerstone of modern physiology. “It was Bernard’s view that we achieve a free and independent life, physically and mentally, because of the constancy of the composition of our internal environment” (Smith 1961:1). Direct contact between the gills and water makes ion, water, and acid-base balance especially challenging and important to fish and, in turn, makes fish important subjects for understanding the evolution and control of all of these homeostatic processes.</p><p>Several strategies exist within fishes for regulating ion concentrations in the blood relative to external (environmental) salt concentrations. Hagfishes, which are one extant group representing the ancestral jawless condition of vertebrates, are restricted to seawater (SW) and have an osmoconforming strategy in which the internal (blood) and external osmotic concentrations are very similar (Currie and Edwards 2010), but important differences do exist (Sardella et al. 2009). Lampreys are the other group of extant jawless fishes and either live wholly in freshwater (FW) or are<span>&nbsp;</span><strong>anadromous</strong>. Lampreys have an osmoregulatory strategy in which the internal concentrations of ions are approximately one-third that of SW (Reis-Santos et al. 2008). Their underlying mechanisms of ion transport and osmoregulation appear to be nearly identical to those of the more recently evolved ray-finned fishes (Figure 9.1), which have adopted a similar osmoregulatory strategy. Elasmobranchs and coelacanths in SW retain high levels of urea in their plasma and are osmoconformers (Figure 9.2), whereas in the relatively rare instances elasmobranchs are found in FW, they are hyperosmoregulators, maintaining plasma ion levels in excess of environmental levels via mechanisms similar to FW ray-finned fishes (Ballantyne and Robinson 2010).</p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Methods for fish biology","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"American Fisheries Society","doi":"10.47886/9781934874615.ch9","usgsCitation":"McCormick, S.D., Schultz, E., and Brauner, C., 2022, Osmoregulation and acid-base balance., chap. 9 <i>of</i> Methods for fish biology, p. 275-308, https://doi.org/10.47886/9781934874615.ch9.","productDescription":"34 p.","startPage":"275","endPage":"308","ipdsId":"IP-108481","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":412128,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"edition":"2nd edition","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"McCormick, Stephen D. 0000-0003-0621-6200 smccormick@usgs.gov","orcid":"https://orcid.org/0000-0003-0621-6200","contributorId":139214,"corporation":false,"usgs":true,"family":"McCormick","given":"Stephen","email":"smccormick@usgs.gov","middleInitial":"D.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":861975,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schultz, Eric T.","contributorId":298956,"corporation":false,"usgs":false,"family":"Schultz","given":"Eric T.","affiliations":[{"id":64738,"text":"University of CT, Storrs","active":true,"usgs":false}],"preferred":false,"id":861976,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brauner, Colin","contributorId":301092,"corporation":false,"usgs":false,"family":"Brauner","given":"Colin","affiliations":[{"id":36484,"text":"UBC","active":true,"usgs":false}],"preferred":false,"id":861977,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70240308,"text":"70240308 - 2022 - Modeling risk dynamics of contaminants of emerging concern in a temperate-region wastewater effluent-dominated stream","interactions":[],"lastModifiedDate":"2023-02-03T14:45:16.85921","indexId":"70240308","displayToPublicDate":"2022-12-01T08:24:40","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5112,"text":"Environmental Science: Water Research & Technology","active":true,"publicationSubtype":{"id":10}},"title":"Modeling risk dynamics of contaminants of emerging concern in a temperate-region wastewater effluent-dominated stream","docAbstract":"<p><span>Wastewater effluent-dominated streams are becoming increasingly common worldwide, including in temperate regions, with potential impacts on ecological systems and drinking water sources. We recently quantified the occurrence/spatiotemporal dynamics of pharmaceutical mixtures in a representative temperate-region wastewater effluent-dominated stream (Muddy Creek, Iowa) under baseflow conditions and characterized relevant fate processes. Herein, we quantified the ecological risk quotients (RQs) of 19 effluent-derived contaminants of emerging concern (CECs; including: 14 pharmaceuticals, 2 industrial chemicals, and 3 neonicotinoid insecticides) and 1 run-off-derived compound (atrazine) in the stream under baseflow conditions, and estimated the probabilistic risks of effluent-derived CECs under all-flow conditions (</span><i>i.e.</i><span>, including runoff events) using stochastic risk modeling. We determined that 11 out of 20 CECs pose medium-to-high risks to local ecological systems (</span><i>i.e.</i><span>, algae, invertebrates, fish) based on literature-derived acute effects under measured baseflow conditions. Stochastic risk modeling indicated decreased, but still problematic, risk of effluent-derived CECs (</span><i>i.e.</i><span>, RQ ≥ 0.1) under all-flow conditions when runoff events were included. Dilution of effluent-derived chemicals from storm flows thus only minimally decreased risk to aquatic biota in the effluent-dominated stream. We also modeled in-stream transport. Thirteen out of 14 pharmaceuticals persisted along the stream reach (median attenuation rate constant&nbsp;</span><i>k</i><span>&nbsp;&lt; 0.1 h</span><small><sup>−1</sup></small><span>) and entered the Iowa River at elevated concentrations. Predicted and measured concentrations in the drinking water treatment plant were below the human health benchmarks. This study demonstrates the application of probabilistic risk assessments for effluent-derived CECs in a representative effluent-dominated stream under variable flow conditions (when measurements are less practical) and provides an enhanced prediction tool transferable to other effluent-dominated systems.</span></p>","language":"English","publisher":"Royal Society of Chemistry","doi":"10.1039/D2EW00157H","usgsCitation":"Zhi, H., Webb, D.T., Schnoor, J.L., Kolpin, D., Klaper, R.D., Iwanowicz, L., and LeFevre, G.H., 2022, Modeling risk dynamics of contaminants of emerging concern in a temperate-region wastewater effluent-dominated stream: Environmental Science: Water Research & Technology, v. 8, p. 1408-1422, https://doi.org/10.1039/D2EW00157H.","productDescription":"15 p.","startPage":"1408","endPage":"1422","ipdsId":"IP-129637","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":445736,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/9431852","text":"External Repository"},{"id":412670,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Iowa","otherGeospatial":"Muddy Creek","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -91.55039606554381,\n              41.6953124183122\n            ],\n            [\n              -91.54728310759076,\n              41.69428009738749\n            ],\n            [\n              -91.54749768431226,\n              41.69891044541674\n            ],\n            [\n              -91.54924385578545,\n              41.702072402012334\n            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]\n}","volume":"8","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Zhi, Hui","contributorId":225502,"corporation":false,"usgs":false,"family":"Zhi","given":"Hui","email":"","affiliations":[{"id":6768,"text":"University of Iowa","active":true,"usgs":false}],"preferred":false,"id":863353,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Webb, Danielle T.","contributorId":211879,"corporation":false,"usgs":false,"family":"Webb","given":"Danielle","email":"","middleInitial":"T.","affiliations":[{"id":6768,"text":"University of Iowa","active":true,"usgs":false}],"preferred":false,"id":863354,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schnoor, Jerald L","contributorId":302047,"corporation":false,"usgs":false,"family":"Schnoor","given":"Jerald","email":"","middleInitial":"L","affiliations":[{"id":6768,"text":"University of Iowa","active":true,"usgs":false}],"preferred":false,"id":863355,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kolpin, Dana W. 0000-0002-3529-6505","orcid":"https://orcid.org/0000-0002-3529-6505","contributorId":204154,"corporation":false,"usgs":true,"family":"Kolpin","given":"Dana W.","affiliations":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true},{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"preferred":true,"id":863356,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Klaper, Rebecca D.","contributorId":218114,"corporation":false,"usgs":false,"family":"Klaper","given":"Rebecca","email":"","middleInitial":"D.","affiliations":[{"id":18038,"text":"University of Wisconsin, Milwaukee","active":true,"usgs":false}],"preferred":false,"id":863357,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Iwanowicz, Luke 0000-0002-1197-6178 liwanowicz@usgs.gov","orcid":"https://orcid.org/0000-0002-1197-6178","contributorId":302048,"corporation":false,"usgs":true,"family":"Iwanowicz","given":"Luke","email":"liwanowicz@usgs.gov","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":863358,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"LeFevre, Gregory H.","contributorId":211880,"corporation":false,"usgs":false,"family":"LeFevre","given":"Gregory","email":"","middleInitial":"H.","affiliations":[{"id":6768,"text":"University of Iowa","active":true,"usgs":false}],"preferred":true,"id":863359,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70238615,"text":"70238615 - 2022 - Atmospheric circulation drivers of extreme high water level events at Foggy Island Bay, Alaska","interactions":[],"lastModifiedDate":"2022-12-01T14:28:00.803404","indexId":"70238615","displayToPublicDate":"2022-12-01T08:20:04","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5634,"text":"Atmosphere","active":true,"publicationSubtype":{"id":10}},"title":"Atmospheric circulation drivers of extreme high water level events at Foggy Island Bay, Alaska","docAbstract":"The northern coast of Alaska is experiencing significant climatic change enhancing hazards from reduced sea ice and increased coastal erosion. This same region is home to offshore oil/gas activities. Foggy Island Bay is one region along the Beaufort Sea coast with planned offshore oil/gas development that will need to account for the changing climate. High water levels impact infrastructure through coastal erosion and flooding hazards. In this study, 21 high water level events exceeding the top 95th percentile were identified at the gauge in Prudhoe Bay, Alaska (adjacent to Foggy Island Bay) over 1990-2018. All events were associated with strong westerly winds according to weather station records. Low pressure storm systems were found to be a key driver of westerly winds in the region according to downscaled reanalysis and storm track data. A dynamically downscaled global climate model projection from CMIP5 indicates that days with westerly wind events will become frequent by 2100 in the Foggy Island Bay region. Coupled with the anticipated continued decline in sea ice, the northern coast of Alaska may experience more frequent high water events over the next ~80 years.","language":"English","publisher":"MDPI","doi":"10.3390/atmos13111791","usgsCitation":"Bieniek, P., Erikson, L.H., and Kasper, J., 2022, Atmospheric circulation drivers of extreme high water level events at Foggy Island Bay, Alaska: Atmosphere, v. 13, 1791, 17 p., https://doi.org/10.3390/atmos13111791.","productDescription":"1791, 17 p.","ipdsId":"IP-144924","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":445740,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/atmos13111791","text":"Publisher Index Page"},{"id":409922,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Beaufort Sea, Foggy Island Bay, Prudhoe Bay","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -148.80741465739465,\n              70.39723931268995\n            ],\n            [\n              -148.70029566028296,\n              70.4000035945075\n            ],\n            [\n              -148.54373712604283,\n              70.3677303272334\n            ],\n            [\n              -148.4970442298659,\n              70.33540601843683\n            ],\n            [\n              -148.5245106393817,\n              70.31321124176867\n            ],\n            [\n              -148.5217639984302,\n              70.29284489806011\n            ],\n            [\n              -148.3404856956258,\n              70.29377107971973\n            ],\n            [\n              -148.1015279328383,\n              70.39816078157423\n            ],\n            [\n              -148.37344538704474,\n              70.47541577367042\n            ],\n            [\n              -148.7222687878956,\n              70.46715246793207\n            ],\n            [\n              -148.80741465739465,\n              70.39723931268995\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"13","noUsgsAuthors":false,"publicationDate":"2022-10-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Bieniek, Peter A.","contributorId":209850,"corporation":false,"usgs":false,"family":"Bieniek","given":"Peter A.","affiliations":[{"id":38014,"text":"Alaska Climate Science Center, University of Alaska, Fairbanks, AK","active":true,"usgs":false}],"preferred":false,"id":858103,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Erikson, Li H. 0000-0002-8607-7695 lerikson@usgs.gov","orcid":"https://orcid.org/0000-0002-8607-7695","contributorId":149963,"corporation":false,"usgs":true,"family":"Erikson","given":"Li","email":"lerikson@usgs.gov","middleInitial":"H.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":858104,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kasper, Jeremy L. 0000-0003-0975-6114","orcid":"https://orcid.org/0000-0003-0975-6114","contributorId":208630,"corporation":false,"usgs":false,"family":"Kasper","given":"Jeremy L.","affiliations":[{"id":37850,"text":"University of Alaska Fairbanks, Fairbanks, Alaska, UNITED STATES","active":true,"usgs":false}],"preferred":false,"id":858105,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70226741,"text":"70226741 - 2022 - OpenET: Filling a critical data gap in water management for the western United States","interactions":[],"lastModifiedDate":"2024-05-17T16:01:54.302021","indexId":"70226741","displayToPublicDate":"2022-12-01T06:52:20","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2529,"text":"Journal of the American Water Resources Association","active":true,"publicationSubtype":{"id":10}},"title":"OpenET: Filling a critical data gap in water management for the western United States","docAbstract":"<div class=\"abstract-group\"><div class=\"article-section__content en main\"><p>The lack of consistent, accurate information on evapotranspiration (ET) and consumptive use of water by irrigated agriculture is one of the most important data gaps for water managers in the western United States (U.S.) and other arid agricultural regions globally. The ability to easily access information on ET is central to improving water budgets across the West, advancing the use of data-driven irrigation management strategies, and expanding incentive-driven conservation programs. Recent advances in remote sensing of ET have led to the development of multiple approaches for field-scale ET mapping that have been used for local and regional water resource management applications by U.S. state and federal agencies. The OpenET project is a community-driven effort that is building upon these advances to develop an operational system for generating and distributing ET data at a field scale using an ensemble of six well-established satellite-based approaches for mapping ET. Key objectives of OpenET include: Increasing access to remotely sensed ET data through a web-based data explorer and data services; supporting the use of ET data for a range of water resource management applications; and development of use cases and training resources for agricultural producers and water resource managers. Here we describe the OpenET framework, including the models used in the ensemble, the satellite, meteorological, and ancillary data inputs to the system, and the OpenET data visualization and access tools. We also summarize an extensive intercomparison and accuracy assessment conducted using ground measurements of ET from 139 flux tower sites instrumented with open path eddy covariance systems. Results calculated for 24 cropland sites from Phase I of the intercomparison and accuracy assessment demonstrate strong agreement between the satellite-driven ET models and the flux tower ET data. For the six models that have been evaluated to date (ALEXI/DisALEXI, eeMETRIC, geeSEBAL, PT-JPL, SIMS, and SSEBop) and the ensemble mean, the weighted average mean absolute error (MAE) values across all sites range from 13.6 to 21.6 mm/month at a monthly timestep, and 0.74 to 1.07 mm/day at a daily timestep. At seasonal time scales, for all but one of the models the weighted mean total ET is within ±8% of both the ensemble mean and the weighted mean total ET calculated from the flux tower data. Overall, the ensemble mean performs as well as any individual model across nearly all accuracy statistics for croplands, though some individual models may perform better for specific sites and regions. We conclude with three brief use cases to illustrate current applications and benefits of increased access to ET data, and discuss key lessons learned from the development of OpenET.</p></div></div>","language":"English","publisher":"Wiley","doi":"10.1111/1752-1688.12956","usgsCitation":"Melton, F., Huntington, J., Grimm, R., Herring, J., Hall, M., Rollison, D., Erickson, T., Allen, R., Anderson, M., Fisher, J., Kilic, A., Senay, G., Volk, J.M., Hain, C., Johnson, L., Ruhoff, A., Blankenau, P., Bromley, M., Carrara, W., Daudert, B., Doherty, C., Dunkerly, C., Friedrichs, M., Guzman, A., Halverson, G., Hansen, J., Harding, J., Kang, Y., Ketchum, D., Minor, B., Morton, C., Ortega-Salazar, S., Ott, T., Ozdogan, M., Revelle, P., Schull, M., Wang, C., Yang, Y., and Anderson, R.G., 2022, OpenET: Filling a critical data gap in water management for the western United States: Journal of the American Water Resources Association, v. 58, no. 6, p. 971-994, 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,{"id":70239032,"text":"70239032 - 2022 - Habitat-specific foraging by striped bass (Morone saxatilis) in the San Francisco Estuary, California: Implications for tidal restoration","interactions":[],"lastModifiedDate":"2022-12-21T12:51:45.801843","indexId":"70239032","displayToPublicDate":"2022-12-01T06:49:28","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3331,"text":"San Francisco Estuary and Watershed Science","active":true,"publicationSubtype":{"id":10}},"title":"Habitat-specific foraging by striped bass (Morone saxatilis) in the San Francisco Estuary, California: Implications for tidal restoration","docAbstract":"<div id=\"main\"><div data-reactroot=\"\"><div class=\"body\"><div class=\"c-columns--sticky-sidebar\"><div class=\"c-tabs\"><div class=\"c-tabs__content\"><div class=\"c-tabcontent\"><div class=\"c-clientmarkup\"><p>Non-native predatory fish strongly impact aquatic communities, and their impacts can be exacerbated by anthropogenic habitat alterations. Loss of natural habitat and restoration actions reversing habitat loss can modify relationships between non-native predators and prey. Predicting how these relationships will change is often difficult because insufficient information exists on the habitat-specific feeding ecology of non-native predators. To address this information gap, we examined diets of non-native Striped Bass (<i>Morone saxatilis</i>; 63 to 671 mm standard length; estimated age 1-5 yrs) in the San Francisco Estuary during spring and summer in three habitat types – marsh, shoal, and channel – with the marsh habitat type serving as a model for ongoing and future restoration. Based on a prey-specific index of relative importance, Striped Bass diets were dominated by macroinvertebrates in spring and summer (amphipods in spring, decapods and isopods in summer). In spring, diets were relatively consistent across habitats. In summer, marsh diets were dominated by sphaeromatid isopods and shoal/channel diets by idoteid amphipods and decapods. Striped Bass consumed a variety of native and non-native fishes, primarily Prickly Sculpin (<i>Cottus asper</i>) and Gobiidae. The highest importance of fish prey was in the marsh in spring (~40% prey weight), and fish prey comprised less than 25% prey weight in all other season/habitat combinations. Linear discriminant analyses suggested that marsh foraging was prevalent in Striped Bass collected in other habitats, mostly due to the predominance of marsh-associated invertebrates found in the stomachs of individual Striped Bass collected outside of the marsh. Striped Bass diets differ across habitats, with marsh foraging important to Striped Bass regardless of collection location. This information can be used to forecast the potential utilization of restored habitats by this non-native piscivore.</p></div></div></div></div></div></div></div></div>","language":"English","publisher":"University of California","doi":"10.15447/sfews.2022v20iss3art4","usgsCitation":"Young, M.J., Feyrer, F.V., Smith, C.D., and Valentine, D.A., 2022, Habitat-specific foraging by striped bass (Morone saxatilis) in the San Francisco Estuary, California: Implications for tidal restoration: San Francisco Estuary and Watershed Science, v. 20, no. 3, 4, 19 p., https://doi.org/10.15447/sfews.2022v20iss3art4.","productDescription":"4, 19 p.","ipdsId":"IP-136087","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":445755,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.15447/sfews.2022v20iss3art4","text":"Publisher Index Page"},{"id":410853,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Francisco Estuary","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -122.9623048112609,\n              38.36264096351189\n            ],\n            [\n              -122.9623048112609,\n              37.27832534635466\n            ],\n            [\n              -121.2381834959669,\n              37.27832534635466\n            ],\n            [\n              -121.2381834959669,\n              38.36264096351189\n            ],\n            [\n              -122.9623048112609,\n              38.36264096351189\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"20","issue":"3","noUsgsAuthors":false,"publicationDate":"2022-10-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Young, Matthew J. 0000-0001-9306-6866 mjyoung@usgs.gov","orcid":"https://orcid.org/0000-0001-9306-6866","contributorId":206255,"corporation":false,"usgs":true,"family":"Young","given":"Matthew","email":"mjyoung@usgs.gov","middleInitial":"J.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":859791,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Feyrer, Frederick V. 0000-0003-1253-2349 ffeyrer@usgs.gov","orcid":"https://orcid.org/0000-0003-1253-2349","contributorId":178379,"corporation":false,"usgs":true,"family":"Feyrer","given":"Frederick","email":"ffeyrer@usgs.gov","middleInitial":"V.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":859792,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Smith, Collin D. 0000-0003-4184-5686 cdsmith@usgs.gov","orcid":"https://orcid.org/0000-0003-4184-5686","contributorId":3111,"corporation":false,"usgs":true,"family":"Smith","given":"Collin","email":"cdsmith@usgs.gov","middleInitial":"D.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":859793,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Valentine, Dennis A.","contributorId":258067,"corporation":false,"usgs":false,"family":"Valentine","given":"Dennis","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":859794,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70238740,"text":"70238740 - 2022 - Endangered Cape Sable seaside sparrow ecology: Actions towards recovery through landscape-scale ecosystem restoration","interactions":[],"lastModifiedDate":"2022-12-07T12:39:40.852805","indexId":"70238740","displayToPublicDate":"2022-12-01T06:37:28","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1497,"text":"Endangered Species Research","active":true,"publicationSubtype":{"id":10}},"title":"Endangered Cape Sable seaside sparrow ecology: Actions towards recovery through landscape-scale ecosystem restoration","docAbstract":"<p class=\"abstract_block\">Understanding the ecology of endangered taxa and the factors affecting their population growth and decline is imperative for their recovery. In the southeastern USA, the Everglades wetland ecosystem supports a high diversity of species and communities, including many endemic and imperiled taxa, such as the federally endangered Cape Sable seaside sparrow<span>&nbsp;</span><i>Ammospiza maritima mirabilis</i><span>&nbsp;</span>(CSSS). The Everglades, once a completely connected wetland with a slow-moving sheet flow of water, is now compartmentalized into separated wetland units where water distribution is managed year-round. The CSSS is affected by, and at the crux of, many Everglades ecosystem restoration decisions. The CSSS faces conservation challenges, including limited habitat availability, low population numbers, dispersal limitations, and constraints on suitable breeding conditions owing to wetland water levels. Despite these challenges, ecological knowledge of the factors affecting CSSS population numbers in the context of ongoing ecosystem-level restoration can help inform protection of this bird while restoring the Everglades. Existing research shows target hydroperiods between 90 and 210 days, a minimum of 90 consecutive dry days during the breeding season, and non-breeding season fires approximately every 5-10 years may aid in CSSS recovery. There are numerous tools and models to support habitat and water management for the CSSS, and the most recent ecosystem-level water operations plan for the Everglades indicates potential for increased CSSS habitat. Here, we provide a review on the ecology of the CSSS, factors affecting population decline, and ecosystem-level restoration actions that may aid in CSSS recovery.</p>","language":"English","publisher":"Inter-Research","doi":"10.3354/esr01212","usgsCitation":"Benscoter, A., and Romanach, S., 2022, Endangered Cape Sable seaside sparrow ecology: Actions towards recovery through landscape-scale ecosystem restoration: Endangered Species Research, v. 49, p. 199-215, https://doi.org/10.3354/esr01212.","productDescription":"17 p.","startPage":"199","endPage":"215","ipdsId":"IP-138298","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":445757,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3354/esr01212","text":"Publisher Index Page"},{"id":410150,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Dlorida","otherGeospatial":"Everglades","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -82.00201430502638,\n              26.691780992327622\n            ],\n            [\n              -82.00201430502638,\n              24.87241063952405\n            ],\n            [\n              -80.13513135216013,\n              24.87241063952405\n            ],\n            [\n              -80.13513135216013,\n              26.691780992327622\n            ],\n            [\n              -82.00201430502638,\n              26.691780992327622\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"49","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Benscoter, Allison 0000-0003-4205-3808","orcid":"https://orcid.org/0000-0003-4205-3808","contributorId":216194,"corporation":false,"usgs":true,"family":"Benscoter","given":"Allison","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":858457,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Romanach, Stephanie 0000-0003-0271-7825","orcid":"https://orcid.org/0000-0003-0271-7825","contributorId":220761,"corporation":false,"usgs":true,"family":"Romanach","given":"Stephanie","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":858458,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70247379,"text":"70247379 - 2022 - Hybrid broadband ground-motion simulation validation of small magnitude active shallow crustal earthquakes in New Zealand","interactions":[],"lastModifiedDate":"2023-07-31T18:45:24.809351","indexId":"70247379","displayToPublicDate":"2022-11-30T13:27:06","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1436,"text":"Earthquake Spectra","active":true,"publicationSubtype":{"id":10}},"title":"Hybrid broadband ground-motion simulation validation of small magnitude active shallow crustal earthquakes in New Zealand","docAbstract":"<p><span>This article presents a comprehensive validation of the hybrid broadband ground-motion simulation approach (via the commonly used Graves and Pitarka method) in a New Zealand context with small magnitude point source ruptures using an extensive set of 5218 ground motions recorded at 212 sites from 479 active shallow crustal earthquakes across the country. Modifications to the simulation method inferred from a previous New Zealand validation are implemented, and the improvements are explicitly quantified. Empirical ground-motion models are also considered to provide a benchmark for simulation prediction accuracy and precision. Examination of intensity measure residuals identifies that the simulation method modifications lead to reduced model prediction bias and within-event variability and provides evidence toward the use of spatially varying coefficient models for simulation parameters, such as the high-frequency Brune stress parameter. Additional biases identified include, among others, underprediction of significant durations at soft soil sites and overprediction of short-period pseudo-spectral accelerations at stiff alluvial gravel and rock sites due to low-estimated 30 m time-averaged shear-wave velocity values.</span></p>","language":"English","publisher":"SAGE publishing","doi":"10.1177/87552930221109297","usgsCitation":"Lee, R.L., Bradley, B.A., Stafford, P.J., Graves, R., and Rodriguez-Marek, A., 2022, Hybrid broadband ground-motion simulation validation of small magnitude active shallow crustal earthquakes in New Zealand: Earthquake Spectra, v. 38, no. 4, p. 2548-2579, https://doi.org/10.1177/87552930221109297.","productDescription":"32 p.","startPage":"2548","endPage":"2579","ipdsId":"IP-128104","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":419449,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"New Zealand","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"MultiPolygon\",\"coordinates\":[[[[173.02037,-40.91905],[173.24723,-41.332],[173.95841,-40.9267],[174.24759,-41.34916],[174.24852,-41.77001],[173.87645,-42.23318],[173.22274,-42.97004],[172.71125,-43.37229],[173.08011,-43.85334],[172.30858,-43.86569],[171.45293,-44.24252],[171.18514,-44.8971],[170.6167,-45.90893],[169.83142,-46.35577],[169.33233,-46.64124],[168.41135,-46.61994],[167.76374,-46.2902],[166.67689,-46.21992],[166.50914,-45.8527],[167.04642,-45.11094],[168.30376,-44.12397],[168.94941,-43.93582],[169.66781,-43.55533],[170.52492,-43.03169],[171.12509,-42.51275],[171.56971,-41.76742],[171.94871,-41.51442],[172.09723,-40.9561],[172.79858,-40.49396],[173.02037,-40.91905]]],[[[174.61201,-36.1564],[175.33662,-37.2091],[175.3576,-36.52619],[175.80889,-36.79894],[175.95849,-37.55538],[176.7632,-37.88125],[177.43881,-37.96125],[178.01035,-37.57982],[178.51709,-37.69537],[178.27473,-38.58281],[177.97046,-39.16634],[177.20699,-39.14578],[176.93998,-39.44974],[177.03295,-39.87994],[176.88582,-40.06598],[176.50802,-40.60481],[176.01244,-41.28962],[175.23957,-41.68831],[175.0679,-41.42589],[174.65097,-41.28182],[175.22763,-40.45924],[174.90016,-39.90893],[173.82405,-39.50885],[173.85226,-39.1466],[174.5748,-38.79768],[174.74347,-38.02781],[174.69702,-37.38113],[174.29203,-36.71109],[174.319,-36.53482],[173.841,-36.12198],[173.05417,-35.23713],[172.63601,-34.52911],[173.00704,-34.45066],[173.5513,-35.00618],[174.32939,-35.2655],[174.61201,-36.1564]]]]},\"properties\":{\"name\":\"New Zealand\"}}]}","volume":"38","issue":"4","noUsgsAuthors":false,"publicationDate":"2022-08-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Lee, Robin L.","contributorId":261917,"corporation":false,"usgs":false,"family":"Lee","given":"Robin","email":"","middleInitial":"L.","affiliations":[{"id":37172,"text":"University of Canterbury","active":true,"usgs":false}],"preferred":false,"id":879375,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bradley, Brendon A.","contributorId":202814,"corporation":false,"usgs":false,"family":"Bradley","given":"Brendon","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":879376,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stafford, Peter J.","contributorId":261918,"corporation":false,"usgs":false,"family":"Stafford","given":"Peter","email":"","middleInitial":"J.","affiliations":[{"id":24608,"text":"Imperial College London","active":true,"usgs":false}],"preferred":false,"id":879377,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Graves, Robert 0000-0001-9758-453X rwgraves@usgs.gov","orcid":"https://orcid.org/0000-0001-9758-453X","contributorId":140738,"corporation":false,"usgs":true,"family":"Graves","given":"Robert","email":"rwgraves@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":879378,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rodriguez-Marek, Adrian","contributorId":261919,"corporation":false,"usgs":false,"family":"Rodriguez-Marek","given":"Adrian","affiliations":[{"id":12694,"text":"Virginia Tech","active":true,"usgs":false}],"preferred":false,"id":879379,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70238613,"text":"70238613 - 2022 - The influence of drying on the aeolian transport of river-sourced sand","interactions":[],"lastModifiedDate":"2022-12-15T15:56:24.73617","indexId":"70238613","displayToPublicDate":"2022-11-30T08:07:27","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":6503,"text":"Journal of Geophysical Research Earth Surface","active":true,"publicationSubtype":{"id":10}},"title":"The influence of drying on the aeolian transport of river-sourced sand","docAbstract":"<p><span>Transgression and regression of water levels (stages) have impacted the evolution of aeolian landforms and sedimentary deposits throughout geologic history. We studied this phenomenon over a five-day period of reduced flow on the Colorado River in Grand Canyon National Park, AZ, USA, in March 2021. These transient low flows exposed river-channel sand deposits to the air, causing progressive desiccation (drying) and thereby making these deposits susceptible to aeolian transport. We measured aeolian threshold friction velocities (</span><i>u</i><sub><i>*t</i></sub><span>) for sand saltation and PM10 dust emissions, as well as other characteristics, on a subaerially exposed sandbar and downwind aeolian dunefield during each day of the low river flow. The sandbar transitioned from supply-limited to transport-limited aeolian sediment transport conditions during the regression in river water stage. A possible tipping point between the two transport conditions occurred approximately 48 hours after the drop in river flow. The empirically measured&nbsp;</span><i>u</i><sub><i>*t</i></sub><span>&nbsp;decreased as the sandbar sediment dried with increased subaerial exposure time. Theoretical estimates and empirical measurements of&nbsp;</span><i>u</i><sub><i>*t</i></sub><span>&nbsp;corresponded closely on the aeolian dunefield and on the sandbar when it was drier during the third and fourth day of the experiment. Eighty-seven percent of the variability in&nbsp;</span><i>u</i><sub><i>*t</i></sub><span>&nbsp;was explained by empirical models that provide practical estimates of aeolian transport potential of subaerial river sediment deposits using monitoring data that are commonly available in this and other river systems. The work provides theoretical insight into the response of aeolian processes to sediment supply changes driven by periods of anthropogenic activity, drought, and climate change.</span></p>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2022JF006816","usgsCitation":"Sankey, J., Caster, J., Kasprak, A., and Fairley, H.C., 2022, The influence of drying on the aeolian transport of river-sourced sand: Journal of Geophysical Research Earth Surface, v. 127, no. 12, e2022JF006816, 24 p., https://doi.org/10.1029/2022JF006816.","productDescription":"e2022JF006816, 24 p.","ipdsId":"IP-142498","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":445764,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2022jf006816","text":"Publisher Index Page"},{"id":435603,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P91WBUYO","text":"USGS data release","linkHelpText":"Threshold friction velocities for aeolian transport of river-sourced sand, with related moisture content, grain size, topographic, and wind data from Lees Ferry, Arizona"},{"id":409919,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Grand Canyon National Park","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -111.35659478532732,\n              36.965267960408156\n            ],\n            [\n              -114.03110966943333,\n              36.965267960408156\n            ],\n            [\n              -114.03110966943333,\n              35.544550609550456\n            ],\n            [\n              -111.35659478532732,\n              35.544550609550456\n            ],\n            [\n              -111.35659478532732,\n              36.965267960408156\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"127","issue":"12","noUsgsAuthors":false,"publicationDate":"2022-12-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Sankey, Joel B. 0000-0003-3150-4992","orcid":"https://orcid.org/0000-0003-3150-4992","contributorId":261248,"corporation":false,"usgs":true,"family":"Sankey","given":"Joel B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":858099,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Caster, Joshua 0000-0002-2858-1228 jcaster@usgs.gov","orcid":"https://orcid.org/0000-0002-2858-1228","contributorId":199033,"corporation":false,"usgs":true,"family":"Caster","given":"Joshua","email":"jcaster@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":858100,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kasprak, Alan 0000-0001-8184-6128","orcid":"https://orcid.org/0000-0001-8184-6128","contributorId":204162,"corporation":false,"usgs":true,"family":"Kasprak","given":"Alan","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":858101,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fairley, Helen C. 0000-0001-6151-4804 hfairley@usgs.gov","orcid":"https://orcid.org/0000-0001-6151-4804","contributorId":3040,"corporation":false,"usgs":true,"family":"Fairley","given":"Helen","email":"hfairley@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":false,"id":858102,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70238688,"text":"70238688 - 2022 - Defining biologically relevant and hierarchically nested population units to inform wildlife management","interactions":[],"lastModifiedDate":"2022-12-05T13:03:45.51127","indexId":"70238688","displayToPublicDate":"2022-11-30T06:52:31","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Defining biologically relevant and hierarchically nested population units to inform wildlife management","docAbstract":"<div class=\"abstract-group\"><div class=\"article-section__content en main\"><p>Wildlife populations are increasingly affected by natural and anthropogenic changes that negatively alter biotic and abiotic processes at multiple spatiotemporal scales and therefore require increased wildlife management and conservation efforts. However, wildlife management boundaries frequently lack biological context and mechanisms to assess demographic data across the multiple spatiotemporal scales influencing populations. To address these limitations, we developed a novel approach to define biologically relevant subpopulations of hierarchically nested population levels that could facilitate managing and conserving wildlife populations and habitats. Our approach relied on the Spatial “K”luster Analysis by Tree Edge Removal clustering algorithm, which we applied in an agglomerative manner (bottom-to-top). We modified the clustering algorithm using a workflow and population structure tiers from least-cost paths, which captured biological inferences of habitat conditions (functional connectivity), dispersal capabilities (potential connectivity), genetic information, and functional processes affecting movements. The approach uniquely included context of habitat resources (biotic and abiotic) summarized at multiple spatial scales surrounding locations with breeding site fidelity and constraint-based rules (number of sites grouped and population structure tiers). We applied our approach to greater sage-grouse (<i>Centrocercus urophasianus</i>), a species of conservation concern, across their range within the western United States. This case study produced 13 hierarchically nested population levels (akin to cluster levels, each representing a collection of subpopulations of an increasing number of breeding sites). These closely approximated population closure at finer ecological scales (smaller subpopulation extents with fewer breeding sites; cluster levels ≥2), where &gt;92% of individual sage-grouse's time occurred within their home cluster. With available population monitoring data, our approaches can support the investigation of factors affecting population dynamics at multiple scales and assist managers with making informed, targeted, and cost-effective decisions within an adaptive management framework. Importantly, our approach provides the flexibility of including species-relevant context, thereby supporting other wildlife characterized by site fidelity.</p></div></div>","language":"English","publisher":"Wiley","doi":"10.1002/ece3.9565","usgsCitation":"O’Donnell, M.S., Edmunds, D.R., Aldridge, C.L., Heinrichs, J., Monroe, A., Coates, P.S., Prochazka, B.G., Hanser, S.E., and Wiechman, L.A., 2022, Defining biologically relevant and hierarchically nested population units to inform wildlife management: Ecology and Evolution, v. 12, no. 12, e9565, 22 p., https://doi.org/10.1002/ece3.9565.","productDescription":"e9565, 22 p.","ipdsId":"IP-138797","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":445767,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.9565","text":"Publisher Index Page"},{"id":435605,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9X68ADU","text":"USGS data release","linkHelpText":"popcluster: hierarchical population monitoring frameworks, Version 2.0.0"},{"id":435604,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9D1K0LX","text":"USGS data release","linkHelpText":"Hierarchically nested and biologically relevant range-wide monitoring frameworks for greater sage-grouse, western United States"},{"id":410047,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -125.65322907591445,\n              49.7414979702354\n            ],\n            [\n              -125.65322907591445,\n              29.985784975523558\n            ],\n            [\n              -100.48005465232296,\n              29.985784975523558\n            ],\n            [\n              -100.48005465232296,\n              49.7414979702354\n            ],\n            [\n              -125.65322907591445,\n              49.7414979702354\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"12","issue":"12","noUsgsAuthors":false,"publicationDate":"2022-11-30","publicationStatus":"PW","contributors":{"authors":[{"text":"O’Donnell, Michael S. 0000-0002-3488-003X odonnellm@usgs.gov","orcid":"https://orcid.org/0000-0002-3488-003X","contributorId":140876,"corporation":false,"usgs":true,"family":"O’Donnell","given":"Michael","email":"odonnellm@usgs.gov","middleInitial":"S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":858274,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Edmunds, David R. 0000-0002-5212-8271 dedmunds@usgs.gov","orcid":"https://orcid.org/0000-0002-5212-8271","contributorId":152210,"corporation":false,"usgs":true,"family":"Edmunds","given":"David","email":"dedmunds@usgs.gov","middleInitial":"R.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":858275,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Aldridge, Cameron L. 0000-0003-3926-6941 aldridgec@usgs.gov","orcid":"https://orcid.org/0000-0003-3926-6941","contributorId":191773,"corporation":false,"usgs":true,"family":"Aldridge","given":"Cameron","email":"aldridgec@usgs.gov","middleInitial":"L.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":858276,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"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":858277,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Monroe, Adrian P. 0000-0003-0934-8225 amonroe@usgs.gov","orcid":"https://orcid.org/0000-0003-0934-8225","contributorId":152209,"corporation":false,"usgs":true,"family":"Monroe","given":"Adrian P.","email":"amonroe@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":858278,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Coates, Peter S. 0000-0003-2672-9994 pcoates@usgs.gov","orcid":"https://orcid.org/0000-0003-2672-9994","contributorId":3263,"corporation":false,"usgs":true,"family":"Coates","given":"Peter","email":"pcoates@usgs.gov","middleInitial":"S.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":858279,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Prochazka, Brian G. 0000-0001-7270-5550 bprochazka@usgs.gov","orcid":"https://orcid.org/0000-0001-7270-5550","contributorId":174839,"corporation":false,"usgs":true,"family":"Prochazka","given":"Brian","email":"bprochazka@usgs.gov","middleInitial":"G.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":858280,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hanser, Steve E. 0000-0002-4430-2073 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,{"id":70241419,"text":"70241419 - 2022 - Validation of a portable eDNA detection kit for invasive carps","interactions":[],"lastModifiedDate":"2023-03-17T11:39:01.736733","indexId":"70241419","displayToPublicDate":"2022-11-30T06:36:45","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":6476,"text":"Fishes","active":true,"publicationSubtype":{"id":10}},"title":"Validation of a portable eDNA detection kit for invasive carps","docAbstract":"<div class=\"html-p\">Loop-mediated isothermal amplification (LAMP) is a rapid molecular detection technique that has been used as a diagnostic tool for detecting human and animal pathogens for over 20 years and is promising for detecting environmental DNA shed by invasive species. We designed a LAMP assay to detect the invasive carps, silver carp (<span class=\"html-italic\">Hypophthalmichthys molitrix</span>), bighead carp (<span class=\"html-italic\">Hypophthalmichthys nobilis</span>), black carp (<span class=\"html-italic\">Mylopharyngodon piceus</span>), and grass carp (<span class=\"html-italic\">Ctenopharyngodon idella</span>). To determine the sensitivity of the LAMP assay, we determined limit of detection (LOD) for each invasive carp species and compared with the performance of a grass carp quantitative PCR (qPCR) assay in LOD and in a mesocosm study. We used two grass carp densities, 3 juvenile grass carp in one mesocosm and 33 juvenile grass carp in the other. Prior to adding grass carp to the mesocosms, we added 68 kg of fathead minnows (<span class=\"html-italic\">Pimephales promelas</span>) to each mesocosm to simulate farm ponds used for raising bait fish. We filtered 500 mL of water per sample to compare LAMP and qPCR analysis, and we collected 50 mL grab samples that were only analyzed using qPCR to gain additional data using a higher-throughput method to monitor environmental DNA (eDNA) levels throughout the study period. No eDNA for any of the four invasive carp species was detected in water collected from the mesocosms during the three days prior to adding grass carp. Forty-eight hours after grass carp addition to mesocosms, we detected grass carp eDNA in the mesocosm containing 33 grass carp using the LAMP assay. However, we failed to detect any grass carp DNA in the mesocosm containing 3 grass carp with the LAMP assay throughout the study. We analyzed the data using an occupancy model and found that the 500 mL filter samples yielded a higher eDNA capture probability than 50 mL grab samples in the mesocosm containing three grass carp but had similar eDNA capture probability in the mesocosm containing 33 grass carp. Both LAMP and qPCR reliably detected grass carp eDNA 2 days after grass carp addition, but detections were more consistent with qPCR. The LAMP assay may have utility for certain niche uses because it can be used to rapidly analyze eDNA samples and is robust to inhibition, despite having some limitations.</div>","language":"English","publisher":"MDPI","doi":"10.3390/fishes7060363","usgsCitation":"Kageyama, S.A., Hoogland, M.R., Tajjioui, T., Schreier, T.M., Erickson, R.A., and Merkes, C.M., 2022, Validation of a portable eDNA detection kit for invasive carps: Fishes, v. 7, no. 6, 363, 18 p., https://doi.org/10.3390/fishes7060363.","productDescription":"363, 18 p.","ipdsId":"IP-125471","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":445775,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/fishes7060363","text":"Publisher Index Page"},{"id":435608,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9NICB9V","text":"USGS data release","linkHelpText":"Analysis of Grass Carp eDNA Data"},{"id":414328,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7","issue":"6","noUsgsAuthors":false,"publicationDate":"2022-11-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Kageyama, Stacie A. 0000-0003-4185-3627 skageyama@usgs.gov","orcid":"https://orcid.org/0000-0003-4185-3627","contributorId":195991,"corporation":false,"usgs":true,"family":"Kageyama","given":"Stacie","email":"skageyama@usgs.gov","middleInitial":"A.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":866802,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hoogland, Matthew Regh 0000-0002-5340-6915","orcid":"https://orcid.org/0000-0002-5340-6915","contributorId":303225,"corporation":false,"usgs":true,"family":"Hoogland","given":"Matthew","email":"","middleInitial":"Regh","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":866803,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tajjioui, Tariq 0000-0002-0113-0451","orcid":"https://orcid.org/0000-0002-0113-0451","contributorId":215091,"corporation":false,"usgs":true,"family":"Tajjioui","given":"Tariq","email":"","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":866804,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schreier, Theresa M. 0000-0001-7722-6292 tschreier@usgs.gov","orcid":"https://orcid.org/0000-0001-7722-6292","contributorId":3344,"corporation":false,"usgs":true,"family":"Schreier","given":"Theresa","email":"tschreier@usgs.gov","middleInitial":"M.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":866805,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Erickson, Richard A. 0000-0003-4649-482X rerickson@usgs.gov","orcid":"https://orcid.org/0000-0003-4649-482X","contributorId":5455,"corporation":false,"usgs":true,"family":"Erickson","given":"Richard","email":"rerickson@usgs.gov","middleInitial":"A.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":866806,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Merkes, Christopher M. 0000-0001-8191-627X cmerkes@usgs.gov","orcid":"https://orcid.org/0000-0001-8191-627X","contributorId":139516,"corporation":false,"usgs":true,"family":"Merkes","given":"Christopher","email":"cmerkes@usgs.gov","middleInitial":"M.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":866807,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70256596,"text":"70256596 - 2022 - Demographic effects of a megafire on a declining prairie grouse in the mixed-grass prairie","interactions":[],"lastModifiedDate":"2024-08-15T11:00:41.931373","indexId":"70256596","displayToPublicDate":"2022-11-30T05:56:11","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Demographic effects of a megafire on a declining prairie grouse in the mixed-grass prairie","docAbstract":"<p><span>Recent studies have documented benefits of small, prescribed fire and wildfire for grassland-dependent wildlife, such as lesser prairie-chickens (</span><i>Tympanuchus pallidicintus</i><span>), but wildlife demographic response to the scale and intensity of megafire (wildfire &gt;40,000 ha) in modern, fragmented grasslands remains unknown. Limited available grassland habitat makes it imperative to understand if increasing frequency of megafires could further reduce already declining lesser prairie-chicken populations, or if historical evolutionary interactions with fire make lesser prairie-chickens resilient. To evaluate lesser prairie-chicken demographic response to megafires, we compared lek counts, nest density, and survival rates of adults, nests, and chicks before (2014–2016) and after (2018–2020) a 2017 megafire in the mixed-grass prairie of Kansas, USA (Starbuck fire ~254,000 ha). There was a 67% decline in attending males on leks post-fire and a 57% decline in occupied leks post-fire. Despite population declines as indicated by lek counts, adult female breeding season survival (</span>Ŝ<span>) was similar pre- (</span>Ŝ<span>&nbsp;=&nbsp;0.65 ± 0.08 [SE]) and post-fire (0.61 ± 0.08), as was chick survival (pre-fire: 0.23 ± 0.07; post-fire: 0.27 ± 0.11). Nest survival appeared lower post-fire (pre-fire: 0.38 ± 0.06; post-fire: 0.20 ± 0.06), but did not differ at the 95% confidence interval. Nest density of marked females declined 73% in areas burned by megafire. Although lesser prairie-chickens persisted in the study area and we documented minimal effects on most demographic rates, reduced lesser prairie-chicken abundance and reproductive output suggests full recovery may take &gt;3 years. Increased propensity for megafire resulting from suppression of smaller fires, compounded by climate change and woody encroachment, may impose a short-term (3–5&nbsp;year) threat to already declining lesser prairie-chicken populations.</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/ece3.9544","usgsCitation":"Parke, N.J., Sullin, D.S., Haukos, D.A., Fricke, K., Hagen, C., and Ahlers, A.A., 2022, Demographic effects of a megafire on a declining prairie grouse in the mixed-grass prairie: Ecology and Evolution, v. 12, no. 12, e9544, 16 p., https://doi.org/10.1002/ece3.9544.","productDescription":"e9544, 16 p.","ipdsId":"IP-142934","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":445778,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.9544","text":"Publisher Index Page"},{"id":432681,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Kansas, Oklahoma","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -101.54073970102226,\n              37.75193745545033\n            ],\n            [\n              -101.54073970102226,\n              36.24283843115835\n            ],\n            [\n              -98.50851313852192,\n              36.24283843115835\n            ],\n            [\n              -98.50851313852192,\n              37.75193745545033\n            ],\n            [\n              -101.54073970102226,\n              37.75193745545033\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"12","issue":"12","noUsgsAuthors":false,"publicationDate":"2022-11-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Parke, Nicholas J.","contributorId":341309,"corporation":false,"usgs":false,"family":"Parke","given":"Nicholas","email":"","middleInitial":"J.","affiliations":[{"id":12661,"text":"Kansas State University","active":true,"usgs":false}],"preferred":false,"id":908215,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sullin, Daniel S.","contributorId":341310,"corporation":false,"usgs":false,"family":"Sullin","given":"Daniel","email":"","middleInitial":"S.","affiliations":[{"id":12661,"text":"Kansas State University","active":true,"usgs":false}],"preferred":false,"id":908216,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Haukos, David A. 0000-0001-5372-9960 dhaukos@usgs.gov","orcid":"https://orcid.org/0000-0001-5372-9960","contributorId":3664,"corporation":false,"usgs":true,"family":"Haukos","given":"David","email":"dhaukos@usgs.gov","middleInitial":"A.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":908217,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fricke, Kent A.","contributorId":341311,"corporation":false,"usgs":false,"family":"Fricke","given":"Kent A.","affiliations":[{"id":81167,"text":"Kansas Department of Wildlife and Parks","active":true,"usgs":false}],"preferred":false,"id":908218,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hagen, Christian A.","contributorId":341312,"corporation":false,"usgs":false,"family":"Hagen","given":"Christian A.","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":908219,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ahlers, Adam A.","contributorId":341313,"corporation":false,"usgs":false,"family":"Ahlers","given":"Adam","email":"","middleInitial":"A.","affiliations":[{"id":12661,"text":"Kansas State University","active":true,"usgs":false}],"preferred":false,"id":908220,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
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