{"pageNumber":"144","pageRowStart":"3575","pageSize":"25","recordCount":41054,"records":[{"id":70255087,"text":"70255087 - 2023 - Invasive predator diet plasticity has implications for native fish conservation and invasive species suppression","interactions":[],"lastModifiedDate":"2024-06-12T23:21:01.782976","indexId":"70255087","displayToPublicDate":"2023-02-24T18:16:51","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Invasive predator diet plasticity has implications for native fish conservation and invasive species suppression","docAbstract":"<div class=\"abstract toc-section abstract-type-\"><div class=\"abstract-content\"><p>Diet plasticity is a common behavior exhibited by piscivores to sustain predator biomass when preferred prey biomass is reduced. Invasive piscivore diet plasticity could complicate suppression success; thus, understanding invasive predator consumption is insightful to meeting conservation targets. Here, we determine if diet plasticity exists in an invasive apex piscivore and whether plasticity could influence native species recovery benchmarks and invasive species suppression goals. We compared diet and stable isotope signatures of invasive lake trout and native Yellowstone cutthroat trout (cutthroat trout) from Yellowstone Lake, Wyoming, U.S.A. as a function of no, low-, moderate-, and high-lake trout density states. Lake trout exhibited plasticity in relation to their density; consumption of cutthroat trout decreased 5-fold (diet proportion from 0.89 to 0.18) from low- to high-density state. During the high-density state, lake trout switched to amphipods, which were also consumed by cutthroat trout, resulting in high diet overlap (Schoener’s index value, D = 0.68) between the species. As suppression reduced lake trout densities (moderate-density state), more cutthroat trout were consumed (proportion of cutthroat trout = 0.42), and diet overlap was released between the species (D = 0.30). A shift in lake trout δ<sup>13</sup>C signatures from the high- to the moderate-density state also corroborated increased consumption of cutthroat trout and lake trout diet plasticity. Observed declines in lake trout are not commensurate with expected cutthroat trout recovery due to lake trout diet plasticity. The abundance of the native species in need of conservation may take longer to recover due to the diet plasticity of the invasive species. The changes observed in diet, diet overlap, and isotopes associated with predator suppression provides more insight into conservation and suppression dynamics than using predator and prey biomass alone. By understanding these dynamics, we can better prepare conservation programs for potential feedbacks caused by invasive species suppression.</p></div></div><div id=\"figure-carousel-section\"><br></div>","language":"English","publisher":"PLoS","doi":"10.1371/journal.pone.0279099","usgsCitation":"Glassic, H., Guy, C.S., Tronstad, L.M., Lujan, D., Briggs, M.A., Albertson, L.K., and Koel, T., 2023, Invasive predator diet plasticity has implications for native fish conservation and invasive species suppression: PLoS ONE, v. 18, no. 2, e0279099, 22 p., https://doi.org/10.1371/journal.pone.0279099.","productDescription":"e0279099, 22 p.","ipdsId":"IP-130493","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":444368,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0279099","text":"Publisher Index Page"},{"id":430052,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"18","issue":"2","noUsgsAuthors":false,"publicationDate":"2023-02-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Glassic, Hayley C.","contributorId":338576,"corporation":false,"usgs":false,"family":"Glassic","given":"Hayley C.","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":903373,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Guy, Christopher S. 0000-0002-9936-4781 cguy@usgs.gov","orcid":"https://orcid.org/0000-0002-9936-4781","contributorId":2876,"corporation":false,"usgs":true,"family":"Guy","given":"Christopher","email":"cguy@usgs.gov","middleInitial":"S.","affiliations":[{"id":5062,"text":"Office of the Chief Scientist for Ecosystems","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":903374,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tronstad, Lusha M.","contributorId":338578,"corporation":false,"usgs":false,"family":"Tronstad","given":"Lusha","email":"","middleInitial":"M.","affiliations":[{"id":36628,"text":"University of Wyoming","active":true,"usgs":false}],"preferred":false,"id":903376,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lujan, Dominique R.","contributorId":286901,"corporation":false,"usgs":false,"family":"Lujan","given":"Dominique R.","affiliations":[{"id":36628,"text":"University of Wyoming","active":true,"usgs":false}],"preferred":false,"id":903590,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Briggs, Michelle A.","contributorId":338579,"corporation":false,"usgs":false,"family":"Briggs","given":"Michelle","email":"","middleInitial":"A.","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":903377,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Albertson, Lindsey K.","contributorId":338581,"corporation":false,"usgs":false,"family":"Albertson","given":"Lindsey","email":"","middleInitial":"K.","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":903378,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Koel, Todd M.","contributorId":338583,"corporation":false,"usgs":false,"family":"Koel","given":"Todd M.","affiliations":[{"id":36976,"text":"U.S. National Park Service","active":true,"usgs":false}],"preferred":false,"id":903379,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70240796,"text":"sir20235003 - 2023 - Status and trends of total nitrogen and total phosphorus concentrations, loads, and yields in streams of Mississippi, water years 2008–18","interactions":[],"lastModifiedDate":"2026-02-24T18:36:28.127594","indexId":"sir20235003","displayToPublicDate":"2023-02-24T07:30:00","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-5003","displayTitle":"Status and Trends of Total Nitrogen and Total Phosphorus Concentrations, Loads, and Yields in Streams of Mississippi, Water Years 2008–18","title":"Status and trends of total nitrogen and total phosphorus concentrations, loads, and yields in streams of Mississippi, water years 2008–18","docAbstract":"<p>To assess the status and trends of conditions of surface waters throughout Mississippi, the U.S. Geological Survey, in cooperation with the Mississippi Department of Environmental Quality (MDEQ), summarized concentrations and estimated loads, yields, trends, and spatial and temporal patterns of total nitrogen (TN) and total phosphorus (TP) at 20 stream sites in MDEQ’s ambient water-quality monitoring network and 2 stream sites in the U.S. Geological Survey’s National Water-Quality Assessment Project’s monitoring network.</p><p>Comparison of streamflow at the time of water-quality sample collection to flow-duration curves for each site showed that samples were relatively evenly spread over a wide range of flows, indicating that load estimations were representative of a wide range of flows. Relation of streamflow to concentrations of TN and TP varied among sites and land use. Sites with high agriculture land use in the drainage basin tended to have a positive correlation between streamflow and concentration, suggesting influence of event-driven nonpoint-source runoff. Sites near urban (developed) areas tended to have a negative correlation between streamflow and concentration, suggesting chronic point-source influences during low-flow conditions. Sites with high forest land use and lower agriculture and urban (developed) land use showed little to no association between streamflow and concentration.</p><p>Seasonal distributions of concentrations of TN and TP also corresponded closely with variations in land use. Sites near urban (developed) land had the highest concentrations in late summer and fall, sites with a high percentage of agricultural land had the highest concentrations in the spring, and sites that were primarily forested or with little developed land did not exhibit substantial changes in concentration across seasons.</p><p>Eight sites had statistical likelihoods for upward trends of TN loads, and seven sites had statistical likelihoods for downward trends. Trends in TN loads at six sites were considered “about as likely as not,” meaning that a site has an equal chance of having an upward or downward trend. Trend results of mean annual flow-normalized loads of TP for the period of analysis (2008–18) showed that 16 sites had upward trends, 3 sites had downward trends, and 2 sites were considered “about as likely as not.”</p><p>Results from our study were compared to results from existing regional models to assess accuracy of predictions at a local scale. Comparisons of yields predicted from 2012 regional-scale SPAtially Referenced Regressions on Watershed attributes (SPARROW) to results from this study showed the 2012 SPARROW-predicted estimates varied in consistency with results from this study. The 2012 SPARROW-prediction model underestimated TN yields, more often and by a slightly larger degree, more than it overestimated TN yields. The 2012 SPARROW-predicted model tended to underestimate yields at study sites with higher yields. All four sites in the predominantly agricultural area of northwest Mississippi, locally known as the Mississippi Delta, were underestimated by 2012 SPARROW. For TP, yield comparisons at sites with lower yields were consistent, yields at sites with midrange yields tended to be overestimated by SPARROW, and yields at sites with high yields tended to be underestimated by SPARROW. TP yields at four sites in the Mississippi Delta were underestimated by the 2012 SPARROW-predicted model.</p><p>Results of select sites from our study were also compared to other published load estimates from an earlier time period to evaluate possible trends. Comparison of TN yields at four sites and TP yields at three sites from the study-derived estimates to estimates made from data spanning 1993–2004 showed decreasing TN yields at all four sites and decreasing TP yields at two of three sites, with increasing yields of TP at the Yazoo River lower site. Also, a third comparison of the TN and TP yields of the Yazoo River lower site of this study to estimates made from data spanning 1996–97 showed decreasing TN yields but similar TP yields. This suggests that TN yields may have decreased over the last 20–30 years, but TP yields remain constant or are increasing.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235003","issn":"ISSN 2328-0328","collaboration":"Prepared in cooperation with the Mississippi Department of Environmental Quality","usgsCitation":"Hicks, M.B., Crain, A.S., and Segrest, N.G., 2023, Status and trends of total nitrogen and total phosphorus concentrations, loads, and yields in streams of Mississippi, water years 2008–18: U.S. Geological Survey Scientific Investigations Report 2023–5003, 77 p., https://doi.org/10.3133/sir20235003.","productDescription":"Report: x, 77 p.; Data Release; Dataset","numberOfPages":"92","onlineOnly":"Y","ipdsId":"IP-130707","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":413300,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9VV2U70","text":"USGS data release","linkHelpText":"Datasets of streamflow, nutrient concentrations, loads and trends for the Mississippi Ambient Water-Quality Network stations, water years 2008 through 2018"},{"id":413299,"rank":3,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5003/images"},{"id":413297,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5003/sir20235003.pdf","text":"Report","size":"7.56 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":413301,"rank":4,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"—USGS water data for the Nation"},{"id":413352,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5003/sir20235003.XML","text":"Report","size":"481 KB","description":"SIR 20235003 XML"},{"id":413536,"rank":7,"type":{"id":39,"text":"HTML 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 \"}}]}","contact":"<p><a data-mce-href=\"mailto:gs-w-lmg_center_director@usgs.gov\" href=\"mailto:gs-w-lmg_center_director@usgs.gov\">Director</a>, <a data-mce-href=\"https://www.usgs.gov/centers/lmg-water/\" href=\"https://www.usgs.gov/centers/lmg-water/\">Lower Mississippi-Gulf Water Science Center</a><br>U.S. Geological Survey<br>640 Grassmere Park, Suite 100<br>Nashville, TN 37211</p><p><a data-mce-href=\"../contact\" href=\"../contact\">Contact Pubs Warehouse</a></p>","tableOfContents":"<ul><li>Abstract</li><li>Introduction</li><li>Data Collection </li><li>Hydrology and Water Quality </li><li>Trends in Streamflow and Nutrient Loads </li><li>Comparing Study Results to Other Published Nutrient Annual Yields and 2012 SPARROW Model Estimates </li><li>Summary and Conclusions </li><li>References Cited </li><li>Appendix 1</li></ul>","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"publishedDate":"2023-02-24","noUsgsAuthors":false,"publicationDate":"2023-02-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Hicks, Matthew B. 0000-0001-5516-0296 mhicks@usgs.gov","orcid":"https://orcid.org/0000-0001-5516-0296","contributorId":3778,"corporation":false,"usgs":true,"family":"Hicks","given":"Matthew","email":"mhicks@usgs.gov","middleInitial":"B.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":864853,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Crain, Angela S. 0000-0003-0969-6238 ascrain@usgs.gov","orcid":"https://orcid.org/0000-0003-0969-6238","contributorId":3090,"corporation":false,"usgs":true,"family":"Crain","given":"Angela","email":"ascrain@usgs.gov","middleInitial":"S.","affiliations":[{"id":354,"text":"Kentucky Water Science Center","active":true,"usgs":true},{"id":27231,"text":"Indiana-Kentucky Water Science Center","active":true,"usgs":true}],"preferred":true,"id":864854,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Segrest, Natalie G.","contributorId":302617,"corporation":false,"usgs":false,"family":"Segrest","given":"Natalie","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":864855,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70248807,"text":"70248807 - 2023 - The drift history of the Dharwar Craton and India from 2.37 Ga to 1.01 Ga with refinements for an initial Rodinia configuration","interactions":[],"lastModifiedDate":"2023-09-21T12:08:24.115073","indexId":"70248807","displayToPublicDate":"2023-02-24T07:07:15","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1814,"text":"Geoscience Frontiers","active":true,"publicationSubtype":{"id":10}},"title":"The drift history of the Dharwar Craton and India from 2.37 Ga to 1.01 Ga with refinements for an initial Rodinia configuration","docAbstract":"<div id=\"ab010\" class=\"abstract author\"><div id=\"as010\"><p id=\"sp0010\"><span>Coupled paleomagnetic and geochronologic data derived from mafic dykes provide valuable records of continental movement. To reconstruct the Proterozoic paleogeographic history of Peninsular India, we report paleomagnetic directions and U-Pb&nbsp;zircon&nbsp;ages from twenty-nine mafic dykes in the Eastern Dharwar Craton near Hyderabad. Paleomagnetic analysis yielded clusters of directional data that correspond to&nbsp;dyke swarms&nbsp;at 2.37&nbsp;Ga, 2.22&nbsp;Ga, 2.08&nbsp;Ga, 1.89–1.86&nbsp;Ga, 1.79&nbsp;Ga, and a previously undated dual polarity magnetization. We report new positive baked contact tests for the 2.08&nbsp;Ga swarm and the 1.89–1.86&nbsp;Ga swarm(s), and a new inverse baked contact test for the 2.08&nbsp;Ga swarm. Our results promote the 2.08&nbsp;Ga Dharwar Craton paleomagnetic pole (43.1° N, 184.5° E; A95&nbsp;=&nbsp;4.3°) to a reliability score of&nbsp;</span><i>R</i><span>&nbsp;=&nbsp;7 and suggest a position for the Dharwar Craton at 1.79&nbsp;Ga based on a&nbsp;virtual geomagnetic pole&nbsp;(VGP) at 33.0° N, 347.5° E (a95&nbsp;=&nbsp;16.9°,&nbsp;</span><i>k</i>&nbsp;=&nbsp;221,<span>&nbsp;</span><i>N</i>&nbsp;=&nbsp;2). The new VGP for the Dharwar Craton provides support for the union of the Dharwar, Singhbhum, and Bastar Cratons in the Southern India Block by at least 1.79&nbsp;Ga. Combined new and published northeast-southwest moderate-steep dual polarity directions from Dharwar Craton dykes define a new paleomagnetic pole at 20.6° N, 233.1° E (A95&nbsp;=&nbsp;9.2°,<span>&nbsp;</span><i>N</i>&nbsp;=&nbsp;18;<span>&nbsp;</span><i>R</i>&nbsp;=&nbsp;5). Two dykes from this group yielded 1.05–1.01&nbsp;Ga<span>&nbsp;</span><sup>207</sup>Pb/<sup>206</sup>Pb zircon ages and this range is taken as the age of the new paleomagnetic pole. A comparison of the previously published poles with our new 1.05–1.01&nbsp;Ga pole shows India shifting from equatorial to higher (southerly) latitudes from 1.08 Ga to 1.01&nbsp;Ga as a component of Rodinia.</p></div></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.gsf.2023.101581","usgsCitation":"Miller, S.R., Meert, J., Pivarunas, A.F., Sinha, A.K., Pandit, M.K., Mueller, P.A., and Kamenov, G., 2023, The drift history of the Dharwar Craton and India from 2.37 Ga to 1.01 Ga with refinements for an initial Rodinia configuration: Geoscience Frontiers, v. 14, no. 4, 101581, 25 p., https://doi.org/10.1016/j.gsf.2023.101581.","productDescription":"101581, 25 p.","ipdsId":"IP-138043","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":444369,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.gsf.2023.101581","text":"Publisher Index Page"},{"id":421019,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"14","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Miller, Scott R 0000-0001-6710-2974","orcid":"https://orcid.org/0000-0001-6710-2974","contributorId":329983,"corporation":false,"usgs":false,"family":"Miller","given":"Scott","email":"","middleInitial":"R","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":883735,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Meert, Joseph 0000-0003-0297-3239","orcid":"https://orcid.org/0000-0003-0297-3239","contributorId":329970,"corporation":false,"usgs":false,"family":"Meert","given":"Joseph","email":"","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":883736,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pivarunas, Anthony Francis 0000-0002-0003-2059","orcid":"https://orcid.org/0000-0002-0003-2059","contributorId":301014,"corporation":false,"usgs":true,"family":"Pivarunas","given":"Anthony","email":"","middleInitial":"Francis","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":883737,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sinha, Anup K.","contributorId":329972,"corporation":false,"usgs":false,"family":"Sinha","given":"Anup","email":"","middleInitial":"K.","affiliations":[{"id":78754,"text":"Indian Institute Of Geomagnetism","active":true,"usgs":false}],"preferred":false,"id":883738,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pandit, Manoj K. 0000-0002-0404-3337","orcid":"https://orcid.org/0000-0002-0404-3337","contributorId":329971,"corporation":false,"usgs":false,"family":"Pandit","given":"Manoj","email":"","middleInitial":"K.","affiliations":[{"id":78752,"text":"University of Rajasthan","active":true,"usgs":false}],"preferred":false,"id":883739,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Mueller, Paul A.","contributorId":191457,"corporation":false,"usgs":false,"family":"Mueller","given":"Paul","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":883740,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kamenov, George 0000-0002-6041-6687","orcid":"https://orcid.org/0000-0002-6041-6687","contributorId":329973,"corporation":false,"usgs":false,"family":"Kamenov","given":"George","email":"","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":883741,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70241140,"text":"70241140 - 2023 - Random forest classification of multitemporal Landsat 8 spectral data and phenology metrics for land cover mapping in the Sonoran and Mojave Deserts","interactions":[],"lastModifiedDate":"2025-12-12T14:11:58.742845","indexId":"70241140","displayToPublicDate":"2023-02-24T06:55:40","publicationYear":"2023","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":"Random forest classification of multitemporal Landsat 8 spectral data and phenology metrics for land cover mapping in the Sonoran and Mojave Deserts","docAbstract":"<div class=\"html-p\">Geospatial data and tools evolve as new technologies are developed and landscape change occurs over time. As a result, these data may become outdated and inadequate for supporting critical habitat-related work across the international boundary in the Sonoran and Mojave Deserts Bird Conservation Region (BCR 33) due to the area’s complex vegetation communities and the discontinuity in data availability across the United States (US) and Mexico (MX) border. This research aimed to produce the first 30 m continuous land cover map of BCR 33 by prototyping new methods for desert vegetation classification using the Random Forest (RF) machine learning (ML) method. The developed RF classification model utilized multitemporal Landsat 8 Operational Land Imager spectral and vegetation index data from the period of 2013–2020, and phenology metrics tailored to capture the unique growing seasons of desert vegetation. Our RF model achieved an overall classification F-score of 0.80 and an overall accuracy of 91.68%. Our results portrayed the vegetation cover at a much finer resolution than existing land cover maps from the US and MX portions of the study area, allowing for the separation and identification of smaller habitat pockets, including riparian communities, which are critically important for desert wildlife and are often misclassified or nonexistent in current maps. This early prototyping effort serves as a proof of concept for the ML and data fusion methods that will be used to generate the final high-resolution land cover map of the entire BCR 33 region.</div>","language":"English","publisher":"MDPI","doi":"10.3390/rs15051266","usgsCitation":"Melichar, M., Didan, K., Barreto-Muñoz, A., Duberstein, J., Jimenez Hernandez, E., Crimmins, T., Li, H., Traphagen, M.B., Thomas, K.A., and Nagler, P.L., 2023, Random forest classification of multitemporal Landsat 8 spectral data and phenology metrics for land cover mapping in the Sonoran and Mojave Deserts: Remote Sensing, v. 15, no. 5, 1266, 23 p.; Data Release, https://doi.org/10.3390/rs15051266.","productDescription":"1266, 23 p.; Data Release","ipdsId":"IP-143820","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":435434,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P90SG8YB","text":"USGS data release","linkHelpText":"Random forest classification data developed from multitemporal Landsat 8 spectral data and phenology metrics for a subregion in Sonoran and Mojave Deserts, April 2013 &ndash; December 2020"},{"id":414009,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":444371,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs15051266","text":"Publisher Index Page"}],"country":"Mexico, United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -104.63121376311749,\n              23.05438198271179\n            ],\n            [\n              -104.63121376311749,\n              38.72651029826767\n            ],\n            [\n              -118.8634508626148,\n              38.72651029826767\n            ],\n            [\n              -118.8634508626148,\n              23.05438198271179\n            ],\n            [\n              -104.63121376311749,\n              23.05438198271179\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"15","issue":"5","noUsgsAuthors":false,"publicationDate":"2023-02-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Melichar, Madeline","contributorId":302425,"corporation":false,"usgs":false,"family":"Melichar","given":"Madeline","email":"","affiliations":[{"id":65479,"text":"Vegetation Index and Phenology (VIP) Lab, University of Arizona, Tucson, AZ 85721, USA","active":true,"usgs":false}],"preferred":false,"id":866242,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Didan, Kamel","contributorId":292780,"corporation":false,"usgs":false,"family":"Didan","given":"Kamel","affiliations":[{"id":62999,"text":"Biosystems Engineering, University of Arizona, Tucson, AZ, 85721 USA","active":true,"usgs":false}],"preferred":false,"id":866243,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barreto-Muñoz, Armando","contributorId":239891,"corporation":false,"usgs":false,"family":"Barreto-Muñoz","given":"Armando","affiliations":[{"id":48028,"text":"University of Arizona, Biosystems Engineering, Tucson, AZ, 85721 USA","active":true,"usgs":false}],"preferred":false,"id":866244,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Duberstein, Jennifer N.","contributorId":278642,"corporation":false,"usgs":false,"family":"Duberstein","given":"Jennifer N.","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":866245,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jimenez Hernandez, Eduardo","contributorId":303010,"corporation":false,"usgs":false,"family":"Jimenez Hernandez","given":"Eduardo","email":"","affiliations":[{"id":65600,"text":"Vegetation Index and Phenology (VIP) Lab, University of Arizona, Tucson, AZ 85721, USA; Department of Biosystems Engineering, University of Arizona, Tucson, AZ 85721, USA","active":true,"usgs":false}],"preferred":false,"id":866246,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Crimmins, Theresa 0000-0001-9592-625X","orcid":"https://orcid.org/0000-0001-9592-625X","contributorId":222414,"corporation":false,"usgs":false,"family":"Crimmins","given":"Theresa","email":"","affiliations":[{"id":40537,"text":"USA National Phenology Network, National Coordinating Office; University of Arizona, School of Natural Resources and the Environment","active":true,"usgs":false}],"preferred":false,"id":866247,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Li, Haiquan","contributorId":303011,"corporation":false,"usgs":false,"family":"Li","given":"Haiquan","email":"","affiliations":[{"id":65603,"text":"Department of Biosystems Engineering, University of Arizona, Tucson, AZ 85721, USA","active":true,"usgs":false}],"preferred":false,"id":866248,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Traphagen, Myles B.","contributorId":299076,"corporation":false,"usgs":false,"family":"Traphagen","given":"Myles","email":"","middleInitial":"B.","affiliations":[{"id":64759,"text":"Wildlands Network","active":true,"usgs":false}],"preferred":false,"id":866249,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Thomas, Kathryn A. 0000-0002-7131-8564 kathryn_a_thomas@usgs.gov","orcid":"https://orcid.org/0000-0002-7131-8564","contributorId":167,"corporation":false,"usgs":true,"family":"Thomas","given":"Kathryn","email":"kathryn_a_thomas@usgs.gov","middleInitial":"A.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":866250,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Nagler, Pamela L. 0000-0003-0674-103X pnagler@usgs.gov","orcid":"https://orcid.org/0000-0003-0674-103X","contributorId":1398,"corporation":false,"usgs":true,"family":"Nagler","given":"Pamela","email":"pnagler@usgs.gov","middleInitial":"L.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":866251,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70241049,"text":"70241049 - 2023 - A hidden cost of single species management: Habitat-relationships reveal potential negative effects of conifer removal on a non-target species","interactions":[],"lastModifiedDate":"2023-03-08T15:10:27.21488","indexId":"70241049","displayToPublicDate":"2023-02-23T09:04:56","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1015,"text":"Biological Conservation","active":true,"publicationSubtype":{"id":10}},"title":"A hidden cost of single species management: Habitat-relationships reveal potential negative effects of conifer removal on a non-target species","docAbstract":"<p><span>Land management priorities and decisions may result in population declines for non-target wildlife species. In the western United States, large-scale removal of conifer from sagebrush ecosystems (</span><i>Artemisia</i><span>&nbsp;spp.) is occurring to recover greater sage-grouse (</span><i>Centrocercus urophasianus</i><span>) populations and may result in pinyon jay (</span><i>Gymnorhinus cyanocephalus</i><span>) habitat loss. Jay populations have experienced long-term declines, due to unknown causes, resulting in a recent petition for listing under the Endangered Species Act of 1973. We developed a Bayesian hierarchical model of jay abundance, using 13&nbsp;years of point count data (2008–2020) collected across the western United States, to estimate regional population trends, model habitat requirements, assess conifer removal effects on jays, and generate hypotheses regarding jay population declines. Our model included climate and landcover covariates and regional trends in pinyon jay density. We applied our modeled habitat relationships to map predicted pinyon jay density, given 2008 and 2020 resource conditions, and map density changes from 2008 to 2020. Our results indicate pinyon jay populations are declining within Bird Conservation Region 16. Jay density was positively associated with sagebrush cover, Palmer Drought Severity Index, and pinyon-juniper cover. Conversely, jay populations were negatively associated with Normalized Difference Vegetation Index (NDVI). We found higher pinyon jay densities within locations possessing both sagebrush and pinyon-juniper cover; conditions characteristic of phase I and II conifer encroachment which are preferentially targeted for conifer removal to restore sagebrush communities. Conifer removal, if conducted at locations with high pinyon jay densities, is therefore likely to negatively affect jay abundance.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.biocon.2023.109959","usgsCitation":"Van Lanen, N.J., Monroe, A., and Aldridge, C.L., 2023, A hidden cost of single species management: Habitat-relationships reveal potential negative effects of conifer removal on a non-target species: Biological Conservation, v. 280, 109959, 10 p., https://doi.org/10.1016/j.biocon.2023.109959.","productDescription":"109959, 10 p.","ipdsId":"IP-138764","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":444374,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.biocon.2023.109959","text":"Publisher Index Page"},{"id":435435,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9NIG4UW","text":"USGS data release","linkHelpText":"Predicted Pinyon Jay (Gymnorhinus cyanocephalus) densities across the western United States, 2008-2020"},{"id":413855,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, California, Colorado, Idaho, Kansas, Montana, Nebraska, Nevada, North Dakota, South Dakota, Utah, Wyoming","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -115.41395617933225,\n              35.71066116858752\n            ],\n            [\n              -111.67021215517931,\n              35.905346739347536\n            ],\n            [\n              -108.77088674515161,\n              36.96389200169858\n            ],\n            [\n              -101.86862285960521,\n              37.125401887525115\n            ],\n            [\n              -101.51491491061196,\n              37.52404629916971\n            ],\n            [\n              -101.90911987227537,\n              41.291485987900245\n            ],\n            [\n              -103.26229497324951,\n              42.46761717574853\n            ],\n            [\n              -101.97643578414241,\n              43.25420173811844\n            ],\n            [\n              -102.55180019651098,\n              49.041860323717856\n            ],\n            [\n              -117.14265326477982,\n              49.014048521848\n            ],\n            [\n              -116.95141239209565,\n              46.12283190981066\n            ],\n            [\n              -116.941510874859,\n              40.99815769875613\n            ],\n            [\n              -120.0102098874165,\n              38.93737098892768\n            ],\n            [\n              -120.02540765639762,\n              38.10974034171085\n            ],\n            [\n              -115.41395617933225,\n              35.71066116858752\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"280","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Van Lanen, Nicholas J. 0000-0003-0871-0261","orcid":"https://orcid.org/0000-0003-0871-0261","contributorId":302927,"corporation":false,"usgs":true,"family":"Van Lanen","given":"Nicholas","email":"","middleInitial":"J.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":865859,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Monroe, Adrian P. 0000-0003-0934-8225 amonroe@usgs.gov","orcid":"https://orcid.org/0000-0003-0934-8225","contributorId":152209,"corporation":false,"usgs":true,"family":"Monroe","given":"Adrian P.","email":"amonroe@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":865860,"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":865861,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70241942,"text":"70241942 - 2023 - Changes in mangrove blue carbon under elevated atmospheric CO2","interactions":[],"lastModifiedDate":"2023-03-31T13:41:21.573249","indexId":"70241942","displayToPublicDate":"2023-02-23T08:38:08","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5075,"text":"Ecosystem Health and Sustainability","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Changes in mangrove blue carbon under elevated atmospheric CO<sub>2</sub>","title":"Changes in mangrove blue carbon under elevated atmospheric CO2","docAbstract":"<p><span>While there is consensus that blue carbon ecosystems, such as mangroves, have an important role in mitigating some aspects of global climate change, little is known about mangrove carbon cycling under elevated atmospheric CO</span><sub>2</sub><span>&nbsp;concentrations (</span><i>e</i><span>CO</span><sub>2</sub><span>). Here, we review studies in order to identify pathways for how&nbsp;</span><i>e</i><span>CO</span><sub>2</sub><span>&nbsp;might influence mangrove ecosystem carbon cycling. In general,&nbsp;</span><i>e</i><span>CO</span><sub>2</sub><span>&nbsp;alters plant productivity, species community composition, carbon fluxes, and carbon deposition in ways that enhance mangrove carbon storage with&nbsp;</span><i>e</i><span>CO</span><sub>2</sub><span>. As a result, a negative feedback to climate change exists whereby&nbsp;</span><i>e</i><span>CO</span><sub>2</sub><span>&nbsp;adds to mangrove’s ability to sequester additional carbon, which in turn reduces the rate by which CO</span><sub>2</sub><span>&nbsp;builds. Furthermore,&nbsp;</span><i>e</i><span>CO</span><sub>2</sub><span>&nbsp;affects warming and sea-level rise (SLR) through alternate pathways, which coinfluence the mangrove response in both antagonistic (i.e., warming = greater carbon loss to decomposition) and synergistic (i.e., SLR = greater soil carbon burial) ways.&nbsp;</span><i>e</i><span>CO</span><sub>2</sub><span>&nbsp;is projected to become a more prominent driver in the future before reaching a steady state. However, given the complexity of the interactions of biological and environmental factors with&nbsp;</span><i>e</i><span>CO</span><sub>2</sub><span>, long-term field observations and in&nbsp;situ simulation experiments can help to better understand the mechanisms for proper model initialization to predict future changes in mangrove carbon sequestration.</span></p>","language":"English","publisher":"American Association for the Advancement of Science","doi":"10.34133/ehs.0033","usgsCitation":"Gu, X., Qiao, P., Krauss, K., Lovelock, C.E., Adams, J.B., Chapman, S.K., Jennerjahn, T.C., Lin, Q., and Chen, L., 2023, Changes in mangrove blue carbon under elevated atmospheric CO2: Ecosystem Health and Sustainability, v. 9, 0033, 12 p., https://doi.org/10.34133/ehs.0033.","productDescription":"0033, 12 p.","ipdsId":"IP-146217","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":444376,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.34133/ehs.0033","text":"Publisher Index Page"},{"id":415007,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Gu, Xiaoxuan","contributorId":296950,"corporation":false,"usgs":false,"family":"Gu","given":"Xiaoxuan","email":"","affiliations":[{"id":64251,"text":"College of the Environment and Ecology, Xiamen University","active":true,"usgs":false}],"preferred":false,"id":868298,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Qiao, Peiyang","contributorId":303861,"corporation":false,"usgs":false,"family":"Qiao","given":"Peiyang","email":"","affiliations":[{"id":47617,"text":"Xiamen University, China","active":true,"usgs":false}],"preferred":false,"id":868299,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Krauss, Ken 0000-0003-2195-0729","orcid":"https://orcid.org/0000-0003-2195-0729","contributorId":222378,"corporation":false,"usgs":true,"family":"Krauss","given":"Ken","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":868300,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lovelock, Catherine E.","contributorId":215562,"corporation":false,"usgs":false,"family":"Lovelock","given":"Catherine","email":"","middleInitial":"E.","affiliations":[{"id":39280,"text":"School of Biological Sciences, The University of Queensland","active":true,"usgs":false}],"preferred":false,"id":868301,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Adams, Janine B.","contributorId":303863,"corporation":false,"usgs":false,"family":"Adams","given":"Janine","email":"","middleInitial":"B.","affiliations":[{"id":65919,"text":"Nelson Mandela University (South Africa)","active":true,"usgs":false}],"preferred":false,"id":868302,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Chapman, Samantha K.","contributorId":303864,"corporation":false,"usgs":false,"family":"Chapman","given":"Samantha","email":"","middleInitial":"K.","affiliations":[{"id":12766,"text":"Villanova University","active":true,"usgs":false}],"preferred":false,"id":868303,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Jennerjahn, Tim C.","contributorId":303865,"corporation":false,"usgs":false,"family":"Jennerjahn","given":"Tim","email":"","middleInitial":"C.","affiliations":[{"id":65921,"text":"Leibniz Centre for Tropical Marine Research (ZMT), Germany","active":true,"usgs":false}],"preferred":false,"id":868304,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Lin, Qiulian","contributorId":294476,"corporation":false,"usgs":false,"family":"Lin","given":"Qiulian","email":"","affiliations":[{"id":63579,"text":"Xiamen University","active":true,"usgs":false}],"preferred":false,"id":868305,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Chen, Luzhen","contributorId":194706,"corporation":false,"usgs":false,"family":"Chen","given":"Luzhen","email":"","affiliations":[],"preferred":false,"id":868306,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70241240,"text":"70241240 - 2023 - Combinatorial optimization of earthquake spatial distributions under minimum cumulative stress constraints","interactions":[],"lastModifiedDate":"2023-05-25T15:52:09.064418","indexId":"70241240","displayToPublicDate":"2023-02-23T08:30:12","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Combinatorial optimization of earthquake spatial distributions under minimum cumulative stress constraints","docAbstract":"<p><span>We determine optimal on‐fault earthquake spatial distributions using a combinatorial method that minimizes the long‐term cumulative stress resolved on the fault. An integer‐programming framework was previously developed to determine the optimal arrangement of a millennia‐scale earthquake sample that minimizes the misfit to a target slip rate determined from geodetic data. The resulting cumulative stress from just slip‐rate optimization, however, can greatly exceed fault strength estimates. Therefore, we add an objective function that minimizes cumulative stress and broad stress constraints to limit the solution space. We find that there is a trade‐off in the two objectives: minimizing the cumulative stress on a fault within fault strength limits concentrates earthquakes in specific areas of the fault and results in excursions from the target slip rate. Both slip‐rate and stress objectives can be combined in either a weighted or lexicographic (hierarchical) method. Using a combination of objectives, we demonstrate that a Gutenberg–Richter sample of earthquakes can be arranged on a constant slip‐rate finite fault with minimal stress and slip‐rate residuals. We apply this method to determine the optimal arrangement of earthquakes on the variable slip‐rate Nankai megathrust over 5000&nbsp;yr. The sharp decrease in slip rate at the Tokai section of the fault results in surplus cumulative stress under all scenarios. Using stress optimization alone restricts this stress surplus to the northeast end of the fault at the expense of decreasing the slip rate away from the target slip rate at the southwest end of the fault. A combination of both slip‐rate and stress objectives provides an adequate fit to the data, although alternate model formulations for the fault are needed at the Tokai section to explain persistent excess cumulative stress. In general, incorporating stress objectives and constraints into the integer‐programming framework adds an important aspect of fault physics to the resulting earthquake rupture forecasts.</span></p>","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120220175","usgsCitation":"Geist, E.L., and Parsons, T.E., 2023, Combinatorial optimization of earthquake spatial distributions under minimum cumulative stress constraints: Bulletin of the Seismological Society of America, v. 113, no. 3, p. 1025-1038, https://doi.org/10.1785/0120220175.","productDescription":"14 p.","startPage":"1025","endPage":"1038","ipdsId":"IP-144689","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":414280,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"113","issue":"3","noUsgsAuthors":false,"publicationDate":"2023-02-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Geist, Eric L. 0000-0003-0611-1150","orcid":"https://orcid.org/0000-0003-0611-1150","contributorId":15543,"corporation":false,"usgs":true,"family":"Geist","given":"Eric","email":"","middleInitial":"L.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":866627,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Parsons, Thomas E. 0000-0002-0582-4338 tparsons@usgs.gov","orcid":"https://orcid.org/0000-0002-0582-4338","contributorId":2314,"corporation":false,"usgs":true,"family":"Parsons","given":"Thomas","email":"tparsons@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":866628,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70241040,"text":"70241040 - 2023 - Incorporation of real-time earthquake magnitudes estimated via peak ground displacement scaling in the ShakeAlert Earthquake Early Warning system","interactions":[],"lastModifiedDate":"2023-05-25T15:50:57.475532","indexId":"70241040","displayToPublicDate":"2023-02-23T07:19:56","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Incorporation of real-time earthquake magnitudes estimated via peak ground displacement scaling in the ShakeAlert Earthquake Early Warning system","docAbstract":"<p>The United States earthquake early warning (EEW) system, ShakeAlert®, currently employs two algorithms based on seismic data alone to characterize the earthquake source, reporting the weighted average of their magnitude estimates. Nonsaturating magnitude estimates derived in real time from Global Navigation Satellite System (GNSS) data using peak ground displacement (PGD) scaling relationships offer complementary information with the potential to improve EEW reliability for large earthquakes. We have adapted a method that estimates magnitude from PGD (<a class=\"link link-ref xref-bibr\" data-modal-source-id=\"rf8\">Crowell<span>&nbsp;</span><i>et&nbsp;al.</i>, 2016</a>) for possible production use by ShakeAlert. To evaluate the potential contribution of the modified algorithm, we installed it on the ShakeAlert development system for real‐time operation and for retrospective analyses using a suite of GNSS data that we compiled. Because of the colored noise structure of typical real‐time GNSS positions, observed PGD values drift over time periods relevant to EEW. To mitigate this effect, we implemented logic within the modified algorithm to control when it issues initial and updated PGD‐derived magnitude estimates (<span class=\"inline-formula no-formula-id\"><span>⁠</span><span id=\"MathJax-Element-1-Frame\" class=\"MathJax\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><msub xmlns=&quot;&quot;><mi>M</mi><mi>PGD</mi></msub></math>\"><span id=\"MathJax-Span-1\" class=\"math\"><span id=\"MathJax-Span-2\" class=\"mrow\"><span id=\"MathJax-Span-3\" class=\"msub\"></span></span></span></span></span><span class=\"inline-formula no-formula-id\"><span id=\"MathJax-Element-1-Frame\" class=\"MathJax\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><msub xmlns=&quot;&quot;><mi>M</mi><mi>PGD</mi></msub></math>\"><span id=\"MathJax-Span-1\" class=\"math\"><span><span id=\"MathJax-Span-2\" class=\"mrow\"><span id=\"MathJax-Span-3\" class=\"msub\"><span id=\"MathJax-Span-4\" class=\"mi\">M</span><span id=\"MathJax-Span-5\" class=\"mi\">PGD</span></span></span></span></span><span class=\"MJX_Assistive_MathML\">PGD</span></span>⁠</span><span>), and to quantify&nbsp;</span><span class=\"inline-formula no-formula-id\"><span id=\"MathJax-Element-2-Frame\" class=\"MathJax\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><msub xmlns=&quot;&quot;><mi>M</mi><mi>PGD</mi></msub></math>\"><span id=\"MathJax-Span-6\" class=\"math\"><span><span id=\"MathJax-Span-7\" class=\"mrow\"><span id=\"MathJax-Span-8\" class=\"msub\"><span id=\"MathJax-Span-9\" class=\"mi\">M</span><span id=\"MathJax-Span-10\" class=\"mi\">PGD</span></span></span></span></span><span class=\"MJX_Assistive_MathML\">PGD</span></span></span><span>&nbsp;uncertainty for use in combining it with estimates from other ShakeAlert algorithms running in parallel. Our analysis suggests that, with these strategies, spuriously large&nbsp;</span><span class=\"inline-formula no-formula-id\"><span id=\"MathJax-Element-3-Frame\" class=\"MathJax\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><msub xmlns=&quot;&quot;><mi>M</mi><mi>PGD</mi></msub></math>\"><span id=\"MathJax-Span-11\" class=\"math\"><span><span id=\"MathJax-Span-12\" class=\"mrow\"><span id=\"MathJax-Span-13\" class=\"msub\"><span id=\"MathJax-Span-14\" class=\"mi\">M</span><span id=\"MathJax-Span-15\" class=\"mi\">PGD</span></span></span></span></span><span class=\"MJX_Assistive_MathML\">PGD</span></span></span><span>&nbsp;will seldom be incorporated in ShakeAlert’s magnitude estimate. Retrospective analysis of data from moderate‐to‐great earthquakes demonstrates that the modified algorithm can contribute to better magnitude estimates for&nbsp;</span><span class=\"inline-formula no-formula-id\"><span id=\"MathJax-Element-4-Frame\" class=\"MathJax\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><msub xmlns=&quot;&quot;><mi>M</mi><mi mathvariant=&quot;normal&quot;>w</mi></msub><mo xmlns=&quot;&quot;>&amp;gt;</mo><mn xmlns=&quot;&quot;>7.0</mn></math>\"><span id=\"MathJax-Span-16\" class=\"math\"><span><span id=\"MathJax-Span-17\" class=\"mrow\"><span id=\"MathJax-Span-18\" class=\"msub\"><span id=\"MathJax-Span-19\" class=\"mi\">M</span><span id=\"MathJax-Span-20\" class=\"mi\">w</span></span><span id=\"MathJax-Span-21\" class=\"mo\">&gt;</span><span id=\"MathJax-Span-22\" class=\"mn\">7.0</span></span></span></span><span class=\"MJX_Assistive_MathML\">w&gt;7.0</span></span></span><span>&nbsp;events. GNSS station distribution throughout the ShakeAlert region limits how soon the modified algorithm can begin estimating magnitude in some locations. Furthermore, both the station density and the GNSS noise levels limit the minimum magnitude for which the modified algorithm is likely to contribute to the weighted average. This might be addressed by alternative GNSS processing strategies that reduce noise.</span></p>","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120220181","usgsCitation":"Murray, J.R., Crowell, B.W., Murray, M.H., Ulberg, C.W., McGuire, J.J., Aranha, M., and Hagerty, M., 2023, Incorporation of real-time earthquake magnitudes estimated via peak ground displacement scaling in the ShakeAlert Earthquake Early Warning system: Bulletin of the Seismological Society of America, v. 113, no. 3, p. 1286-1310, https://doi.org/10.1785/0120220181.","productDescription":"26 p.","startPage":"1286","endPage":"1310","ipdsId":"IP-142519","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":435436,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9KXAIRR","text":"USGS data release","linkHelpText":"Input for assessing the impact of noisy data on earthquake magnitude estimates derived from peak ground displacement measured with real-time Global Navigation Satellite System data"},{"id":413763,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"113","issue":"3","noUsgsAuthors":false,"publicationDate":"2023-02-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Murray, Jessica R. 0000-0002-6144-1681 jrmurray@usgs.gov","orcid":"https://orcid.org/0000-0002-6144-1681","contributorId":2759,"corporation":false,"usgs":true,"family":"Murray","given":"Jessica","email":"jrmurray@usgs.gov","middleInitial":"R.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":865797,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Crowell, Brendan W.","contributorId":184207,"corporation":false,"usgs":false,"family":"Crowell","given":"Brendan","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":865798,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Murray, Mark Hunter 0000-0003-4862-5547","orcid":"https://orcid.org/0000-0003-4862-5547","contributorId":300982,"corporation":false,"usgs":true,"family":"Murray","given":"Mark","email":"","middleInitial":"Hunter","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":865799,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ulberg, Carl W 0000-0001-6198-809X","orcid":"https://orcid.org/0000-0001-6198-809X","contributorId":221909,"corporation":false,"usgs":false,"family":"Ulberg","given":"Carl","email":"","middleInitial":"W","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":865800,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McGuire, Jeffrey J. 0000-0001-9235-2166","orcid":"https://orcid.org/0000-0001-9235-2166","contributorId":220939,"corporation":false,"usgs":true,"family":"McGuire","given":"Jeffrey","middleInitial":"J.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":865801,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Aranha, Mario","contributorId":300983,"corporation":false,"usgs":false,"family":"Aranha","given":"Mario","email":"","affiliations":[{"id":33770,"text":"University of California at Berkeley","active":true,"usgs":false}],"preferred":false,"id":865802,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hagerty, Mike","contributorId":300984,"corporation":false,"usgs":false,"family":"Hagerty","given":"Mike","email":"","affiliations":[{"id":65267,"text":"Instrumental Software Technologies, Inc.","active":true,"usgs":false}],"preferred":false,"id":865803,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70240792,"text":"sir20225131 - 2023 - Nutrient and suspended-sediment concentrations, loads, and yields in upper Macoupin Creek, Illinois, 2017–21","interactions":[],"lastModifiedDate":"2026-02-03T21:08:15.22249","indexId":"sir20225131","displayToPublicDate":"2023-02-23T07:16:54","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2022-5131","displayTitle":"Nutrient and Suspended-Sediment Concentrations, Loads, and Yields in Upper Macoupin Creek, Illinois, 2017–21","title":"Nutrient and suspended-sediment concentrations, loads, and yields in upper Macoupin Creek, Illinois, 2017–21","docAbstract":"<p>The U.S. Geological Survey, in cooperation with the Macoupin County Soil and Water Conservation District and the American Farmland Trust, undertook a monitoring effort from 2017 to 2021 in the upper Macoupin Creek watershed. The monitoring effort was to determine and characterize nitrogen, phosphorus, and suspended-sediment concentrations, loads, and yields for a 566.7 square kilometer area of the Macoupin Creek watershed at two locations on upper Macoupin Creek bracketing a segment of the watershed where increased implementation of conservation land-use practices was planned. Two monitoring stations were established, consisting of an upstream site (Macoupin Creek at Highway 108 near Carlinville, Illinois; U.S. Geological Survey streamgage 05586647) and a downstream site (Macoupin Creek at Highway 111 near Summerville, Ill.; U.S. Geological Survey streamgage 05586745). Data collected at these stations included continuous stream discharge and periodic samples for nutrients and suspended sediment. A Weighted Regressions on Time, Discharge, and Season–Kalman model was implemented to estimate daily concentrations for nitrate plus nitrite, total phosphorus, and suspended sediment for both monitoring stations. These daily concentrations were used in conjunction with the continuous stream discharge data to derive estimates of constituent flux, loads, and yields.</p><p>During the study period, the study area subbasin of the upper Macoupin Creek watershed reduced downstream nitrate and total phosphorus cummulative yields by approximately 54 and 21 percent, respectively; however, the cummulative yield of suspended sediment increased by approximately 10 percent from inputs within the study area. These data indicate that nitrate and phosphorus transport is greater from the upstream subbasin and being diluted in the combined subbasin by lower transport from the study area, whereas suspended sediment is being contributed from the study area reach, presumably through surface runoff and streambank and streambed erosion.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, Va.","doi":"10.3133/sir20225131","collaboration":"Prepared in cooperation with the Macoupin County Soil and Water Conservation District and American Farmland Trust","usgsCitation":"Garcia, L.A., Terrio, P.J., and Manaster, A.E., 2023, Nutrient and suspended-sediment concentrations, loads, and yields in upper Macoupin Creek, Illinois, 2017–21: U.S. Geological Survey Scientific Investigations Report 2022–5131, 17 p., https://doi.org/10.3133/sir20225131.","productDescription":"Report: vii, 17 p.; Data Release; Dataset","numberOfPages":"30","onlineOnly":"Y","ipdsId":"IP-144304","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":413286,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5131/images"},{"id":413285,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5131/sir20225131.XML","text":"Report","linkFileType":{"id":8,"text":"xml"}},{"id":413284,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5131/sir20225131.pdf","text":"Report","size":"2.40 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022–5131"},{"id":499487,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114379.htm","linkFileType":{"id":5,"text":"html"}},{"id":413345,"rank":7,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20225131/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":413289,"rank":6,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"—USGS water data for the Nation"},{"id":413283,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5131/coverthb.jpg"},{"id":413288,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P95IC7QS","text":"USGS data release","linkHelpText":"Nutrient and sediment concentrations, loads, and yields in the Upper Macoupin Creek watershed, water years 2018–2021"}],"country":"United States","state":"Illinois","otherGeospatial":"Upper Macoupin Creek","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -90.666,\n              39.5\n            ],\n            [\n              -90.666,\n              39\n            ],\n            [\n              -89.5,\n              39\n            ],\n            [\n              -89.5,\n              39.5\n            ],\n            [\n              -90.666,\n              39.5\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","contact":"<p>Director, <a href=\"https://www.usgs.gov/centers/cm-water\" data-mce-href=\"https://www.usgs.gov/centers/cm-water\">Central Midwest Water Science Center</a><br>U.S. Geological Survey<br>405 North Goodwin <br>Urbana, IL 61801</p><p><a href=\"https://pubs.er.usgs.gov/contact\" data-mce-href=\"../contact\">Contact Pubs Warehouse</a></p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Purpose and Scope</li><li>Methods</li><li>Nutrient and Suspended-Sediment Concentrations, Loads, and Yields</li><li>Summary</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2023-02-23","noUsgsAuthors":false,"publicationDate":"2023-02-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Garcia, Luis A. 0000-0002-0999-625X","orcid":"https://orcid.org/0000-0002-0999-625X","contributorId":300713,"corporation":false,"usgs":true,"family":"Garcia","given":"Luis","email":"","middleInitial":"A.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":864850,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Terrio, Paul J. 0000-0002-1515-9570 pjterrio@usgs.gov","orcid":"https://orcid.org/0000-0002-1515-9570","contributorId":3313,"corporation":false,"usgs":true,"family":"Terrio","given":"Paul","email":"pjterrio@usgs.gov","middleInitial":"J.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":864851,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Manaster, Adam E. 0000-0001-8183-4274","orcid":"https://orcid.org/0000-0001-8183-4274","contributorId":215663,"corporation":false,"usgs":true,"family":"Manaster","given":"Adam E.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":864852,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70246686,"text":"70246686 - 2023 - Vulnerability of estuarine systems in the contiguous United States to water quality change under future climate and land-use","interactions":[],"lastModifiedDate":"2023-07-14T11:53:26.020041","indexId":"70246686","displayToPublicDate":"2023-02-23T06:50:39","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5053,"text":"Earth's Future","active":true,"publicationSubtype":{"id":10}},"title":"Vulnerability of estuarine systems in the contiguous United States to water quality change under future climate and land-use","docAbstract":"<div class=\"article-section__content en main\"><p>Changes in climate and land-use and land-cover (LULC) are expected to influence surface water runoff and nutrient characteristics of estuarine watersheds, but the extent to which estuaries are vulnerable to altered nutrient loading under future conditions is poorly understood. The present work aims to address this gap through the development of a new vulnerability assessment framework that accounts for (a) estuarine exposure to projected changes in total nitrogen (TN) and total phosphorus (TP) loads as a function of LULC and climate change under several scenarios, (b) sensitivity, and (c) adaptive capacity. The framework was applied to 112 estuaries and their contributing watersheds across the contiguous U.S., specifically to look at regional variability in estuarine vulnerability to nutrient loading. Study findings revealed that the largest increases in estuarine nutrient loads are expected in the North and South Atlantic regions and eastern Gulf of Mexico, while the lowest increases are expected in the North and South Pacific regions and the western Gulf of Mexico. However, the North Atlantic and the South Pacific had the highest adaptive capacity, which could potentially counteract the effects of LULC and climate change on nutrient loads. Strong variation in predicted estuarine nutrient loads was observed as a function of climate model projections, while projected LULC changes were more consistently associated with elevated loads. Our findings illustrate the benefits of integrating natural and socio-ecological factors to identify opportunities to develop adaptation plans and policies to mitigate ecological degradation in vitally important estuaries.</p></div>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2022EF002884","usgsCitation":"Montefiore, L.R., Nelson, N., Staudinger, M., and Terando, A., 2023, Vulnerability of estuarine systems in the contiguous United States to water quality change under future climate and land-use: Earth's Future, v. 11, no. 3, e2022EF002884, 24 p., https://doi.org/10.1029/2022EF002884.","productDescription":"e2022EF002884, 24 p.","ipdsId":"IP-141253","costCenters":[{"id":40926,"text":"Southeast Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":444383,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2022ef002884","text":"Publisher Index 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              46.86475\n              ],\n              [\n                -124.39567,\n                47.72017\n              ],\n              [\n                -124.68721,\n                48.18443\n              ],\n              [\n                -124.5661,\n                48.37971\n              ],\n              [\n                -123.12,\n                48.04\n              ],\n              [\n                -122.58736,\n                47.096\n              ],\n              [\n                -122.34,\n                47.36\n              ],\n              [\n                -122.5,\n                48.18\n              ],\n              [\n                -122.84,\n                49\n              ],\n              [\n                -120,\n                49\n              ],\n              [\n                -117.03121,\n                49\n              ],\n              [\n                -116.04818,\n                49\n              ],\n              [\n                -113,\n                49\n              ],\n              [\n                -110.05,\n                49\n              ],\n              [\n                -107.05,\n                49\n              ],\n              [\n                -104.04826,\n                48.99986\n              ],\n              [\n                -100.65,\n                49\n              ],\n              [\n                -97.22872,\n                49.0007\n              ],\n              [\n                -95.15907,\n                49\n              ],\n              [\n                -95.15609,\n                49.38425\n              ],\n              [\n                -94.81758,\n                49.38905\n              ]\n            ]\n          ]\n        ]\n      },\n      \"properties\": {\n        \"name\": \"United States\"\n      }\n    }\n  ]\n}","volume":"11","issue":"3","noUsgsAuthors":false,"publicationDate":"2023-02-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Montefiore, Lise R.","contributorId":316657,"corporation":false,"usgs":false,"family":"Montefiore","given":"Lise","email":"","middleInitial":"R.","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":877948,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nelson, Natalie","contributorId":251870,"corporation":false,"usgs":false,"family":"Nelson","given":"Natalie","affiliations":[{"id":50407,"text":"North Carolina State U","active":true,"usgs":false}],"preferred":false,"id":877949,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Staudinger, Michelle 0000-0002-4535-2005","orcid":"https://orcid.org/0000-0002-4535-2005","contributorId":206655,"corporation":false,"usgs":true,"family":"Staudinger","given":"Michelle","affiliations":[{"id":5080,"text":"Northeast Climate Adaptation Science Center","active":true,"usgs":true}],"preferred":true,"id":877950,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Terando, Adam J. 0000-0002-9280-043X","orcid":"https://orcid.org/0000-0002-9280-043X","contributorId":216875,"corporation":false,"usgs":true,"family":"Terando","given":"Adam J.","affiliations":[{"id":565,"text":"Southeast Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":877951,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70244140,"text":"70244140 - 2023 - Functional stability of vegetation following biocontrol of an invasive riparian shrub","interactions":[],"lastModifiedDate":"2023-06-05T11:32:02.736878","indexId":"70244140","displayToPublicDate":"2023-02-23T06:30:11","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1018,"text":"Biological Invasions","active":true,"publicationSubtype":{"id":10}},"title":"Functional stability of vegetation following biocontrol of an invasive riparian shrub","docAbstract":"<div id=\"Abs1-section\" class=\"c-article-section\"><div id=\"Abs1-content\" class=\"c-article-section__content\"><p>Understanding plant community response to environmental change is a crucial aspect of biological conservation and restoration, but species-based approaches are limited in that they do not reveal the underlying mechanisms driving vegetation dynamics. An understanding of trait-environment relationships is particularly important in the case of invasive species which may alter abiotic conditions and available resources. This study is the first to measure the functional response of riparian plant communities to biocontrol of an invasive species. We focused on an invasive shrub,<span>&nbsp;</span><i>Tamarix</i><span>&nbsp;</span>(saltcedar), that is defoliated by a beetle that was released by the US Department of Agriculture along the Upper Colorado River (southwestern United States). We calculated community weighted means and functional dispersion of individual traits, multivariate functional dispersion and species diversity. We used linear mixed effect models (LME) to compare these metrics at paired vegetation patches dominated and not dominated by<span>&nbsp;</span><i>Tamarix</i><span>&nbsp;</span>during cycles of defoliation and refoliation over eight years. We found that community-weighted average trait values, species diversity and functional dispersion changed little in response to defoliation, and instead seemed to be responding to fluctuations in yearly precipitation. Average height and seed weight were greater in<span>&nbsp;</span><i>Tamarix</i>-dominated patches relative to control patches. Functional dispersion followed a similar trajectory to species diversity, but was a more sensitive indicator of plant community change. We showed that riparian vegetation can be resilient to<span>&nbsp;</span><i>Tamarix</i><span>&nbsp;</span>biocontrol, and that defoliation might not necessarily always lead to substantial changes in ecosystem function.</p></div></div>","language":"English","publisher":"Springer","doi":"10.1007/s10530-022-02967-4","usgsCitation":"Henry, A.L., Gonzalez-Sargas, E., Shafroth, P., Goetz, A.R., and Sher, A.A., 2023, Functional stability of vegetation following biocontrol of an invasive riparian shrub: Biological Invasions, v. 25, p. 1133-1147, https://doi.org/10.1007/s10530-022-02967-4.","productDescription":"15 p.","startPage":"1133","endPage":"1147","ipdsId":"IP-142104","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":417731,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"25","noUsgsAuthors":false,"publicationDate":"2023-02-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Henry, Annie L.","contributorId":196513,"corporation":false,"usgs":false,"family":"Henry","given":"Annie","email":"","middleInitial":"L.","affiliations":[{"id":12651,"text":"University of Denver","active":true,"usgs":false}],"preferred":false,"id":874594,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gonzalez-Sargas, Eduardo","contributorId":306054,"corporation":false,"usgs":false,"family":"Gonzalez-Sargas","given":"Eduardo","email":"","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":874595,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shafroth, Patrick B. 0000-0002-6064-871X","orcid":"https://orcid.org/0000-0002-6064-871X","contributorId":225182,"corporation":false,"usgs":true,"family":"Shafroth","given":"Patrick B.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":874596,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Goetz, Alexander R.B.","contributorId":306056,"corporation":false,"usgs":false,"family":"Goetz","given":"Alexander","email":"","middleInitial":"R.B.","affiliations":[{"id":12651,"text":"University of Denver","active":true,"usgs":false}],"preferred":false,"id":874597,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sher, Anna A.","contributorId":167194,"corporation":false,"usgs":false,"family":"Sher","given":"Anna","email":"","middleInitial":"A.","affiliations":[{"id":12651,"text":"University of Denver","active":true,"usgs":false}],"preferred":false,"id":874598,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70240725,"text":"gip221 - 2023 - The water cycle","interactions":[],"lastModifiedDate":"2023-03-01T20:15:04.190572","indexId":"gip221","displayToPublicDate":"2023-02-22T14:00:00","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":315,"text":"General Information Product","code":"GIP","onlineIssn":"2332-354X","printIssn":"2332-3531","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"221","displayTitle":"The Water Cycle","title":"The water cycle","docAbstract":"An illustrated diagram of the water cycle. This is a modern, updated version of the widely used diagram featured on the USGS Water Science School. Notably, this new water cycle diagram depicts humans and major categories of human water use as key components of the water cycle, in addition to the key pools and fluxes of the hydrologic cycle. 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-122.34,\n                47.36\n              ],\n              [\n                -122.5,\n                48.18\n              ],\n              [\n                -122.84,\n                49\n              ],\n              [\n                -120,\n                49\n              ],\n              [\n                -117.03121,\n                49\n              ],\n              [\n                -116.04818,\n                49\n              ],\n              [\n                -113,\n                49\n              ],\n              [\n                -110.05,\n                49\n              ],\n              [\n                -107.05,\n                49\n              ],\n              [\n                -104.04826,\n                48.99986\n              ],\n              [\n                -100.65,\n                49\n              ],\n              [\n                -97.22872,\n                49.0007\n              ],\n              [\n                -95.15907,\n                49\n              ],\n              [\n                -95.15609,\n                49.38425\n              ],\n              [\n                -94.81758,\n                49.38905\n              ]\n            ]\n          ]\n        ]\n      },\n      \"properties\": {\n        \"name\": \"United States\"\n      }\n    }\n  ]\n}","contact":"<p><a href=\"https://www.usgs.gov/special-topics/earth-mri/\" data-mce-href=\"https://www.usgs.gov/special-topics/earth-mri/\">Earth Mapping Resources Initiative (Earth MRI)</a><br>Mineral Resources Program<br>U.S. Geological Survey<br>913 National Center<br>12201 Sunrise Valley Drive<br>Reston, VA 20192<br>Email: <a href=\"mailto:minerals@usgs.gov\" data-mce-href=\"mailto:minerals@usgs.gov\">minerals@usgs.gov</a></p>","tableOfContents":"<ul><li>Mineral Systems and Deposit Types</li><li>Focus Areas</li><li>Lithium</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2023-02-22","noUsgsAuthors":false,"publicationDate":"2023-02-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Hammarstrom, Jane M. 0000-0003-2742-3460 jhammars@usgs.gov","orcid":"https://orcid.org/0000-0003-2742-3460","contributorId":1226,"corporation":false,"usgs":true,"family":"Hammarstrom","given":"Jane","email":"jhammars@usgs.gov","middleInitial":"M.","affiliations":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true},{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":864689,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kreiner, Douglas C. 0000-0002-4405-1403","orcid":"https://orcid.org/0000-0002-4405-1403","contributorId":220474,"corporation":false,"usgs":true,"family":"Kreiner","given":"Douglas","email":"","middleInitial":"C.","affiliations":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":864692,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dicken, Connie L. 0000-0002-1617-8132 cdicken@usgs.gov","orcid":"https://orcid.org/0000-0002-1617-8132","contributorId":57098,"corporation":false,"usgs":true,"family":"Dicken","given":"Connie","email":"cdicken@usgs.gov","middleInitial":"L.","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":864690,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Woodruff, Laurel G. 0000-0002-2514-9923 woodruff@usgs.gov","orcid":"https://orcid.org/0000-0002-2514-9923","contributorId":2224,"corporation":false,"usgs":true,"family":"Woodruff","given":"Laurel","email":"woodruff@usgs.gov","middleInitial":"G.","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":864691,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70240979,"text":"70240979 - 2023 - The ties that bind the sagebrush biome: Integrating genetic connectivity into range-wide conservation of greater sage-grouse","interactions":[],"lastModifiedDate":"2023-03-03T16:14:14.964283","indexId":"70240979","displayToPublicDate":"2023-02-22T10:10:42","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3908,"text":"Royal Society Open Science","active":true,"publicationSubtype":{"id":10}},"title":"The ties that bind the sagebrush biome: Integrating genetic connectivity into range-wide conservation of greater sage-grouse","docAbstract":"<p><span>Conserving genetic connectivity is fundamental to species persistence, yet rarely is made actionable into spatial planning for imperilled species. Climate change and habitat degradation have added urgency to embrace connectivity into networks of protected areas. Our two-step process integrates a network model with a functional connectivity model, to identify population centres important to maintaining genetic connectivity then to delineate those pathways most likely to facilitate connectivity thereamong for the greater sage-grouse (</span><i>Centrocercus urophasianus</i><span>), a species of conservation concern ranging across eleven western US states and into two Canadian provinces. This replicable process yielded spatial action maps, able to be prioritized by importance to maintaining range-wide genetic connectivity. We used these maps to investigate the efficacy of 3.2 million ha designated as priority areas for conservation (PACs) to encompass functional connectivity. We discovered that PACs encompassed 41.1% of cumulative functional connectivity—twice the amount of connectivity as random—and disproportionately encompassed the highest-connectivity landscapes. Comparing spatial action maps to impedances to connectivity such as cultivation and woodland expansion allows both planning for future management and tracking outcomes from past efforts.</span></p>","language":"English","publisher":"The Royal Society Publishing","doi":"10.1098/rsos.220437","usgsCitation":"Cross, T.B., Tack, J.D., Naugle, D., Schwartz, M.D., Doherty, K., Oyler-McCance, S.J., Pritchert, R.D., and Fedy, B.C., 2023, The ties that bind the sagebrush biome: Integrating genetic connectivity into range-wide conservation of greater sage-grouse: Royal Society Open Science, v. 10, no. 2, 220437, 15 p., https://doi.org/10.1098/rsos.220437.","productDescription":"220437, 15 p.","ipdsId":"IP-136470","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":444387,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1098/rsos.220437","text":"Publisher Index Page"},{"id":435437,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9HI7OGR","text":"USGS data release","linkHelpText":"Greater sage-grouse network-prioritized functional connectivity cumulative current map (raster)"},{"id":413667,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"western United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -103.07007462178439,\n              48.995456978554444\n            ],\n            [\n              -119.8990141514297,\n              48.995456978554444\n            ],\n            [\n              -119.8990141514297,\n              36.393670817249514\n            ],\n            [\n              -103.07007462178439,\n              36.393670817249514\n            ],\n            [\n              -103.07007462178439,\n              48.995456978554444\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"10","issue":"2","noUsgsAuthors":false,"publicationDate":"2023-02-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Cross, Todd B.","contributorId":189267,"corporation":false,"usgs":false,"family":"Cross","given":"Todd","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":865592,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tack, Jason D. jtack@usgs.gov","contributorId":302682,"corporation":false,"usgs":false,"family":"Tack","given":"Jason","email":"jtack@usgs.gov","middleInitial":"D.","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":865593,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Naugle, David E.","contributorId":255114,"corporation":false,"usgs":false,"family":"Naugle","given":"David E.","affiliations":[{"id":51432,"text":"W.A. Franke College of Forestry and Conservation, University of Montana, Missoula, MT, 59812, USA","active":true,"usgs":false}],"preferred":false,"id":865594,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schwartz, Michael D.","contributorId":174566,"corporation":false,"usgs":false,"family":"Schwartz","given":"Michael","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":865595,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Doherty, Kevin E.","contributorId":177793,"corporation":false,"usgs":false,"family":"Doherty","given":"Kevin E.","affiliations":[],"preferred":false,"id":865596,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Oyler-McCance, Sara J. 0000-0003-1599-8769 sara_oyler-mccance@usgs.gov","orcid":"https://orcid.org/0000-0003-1599-8769","contributorId":1973,"corporation":false,"usgs":true,"family":"Oyler-McCance","given":"Sara","email":"sara_oyler-mccance@usgs.gov","middleInitial":"J.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":865597,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Pritchert, Ronald D.","contributorId":218059,"corporation":false,"usgs":false,"family":"Pritchert","given":"Ronald","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":865598,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Fedy, Brad C.","contributorId":140877,"corporation":false,"usgs":false,"family":"Fedy","given":"Brad","email":"","middleInitial":"C.","affiliations":[{"id":6655,"text":"University of Waterloo","active":true,"usgs":false}],"preferred":false,"id":865599,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70244045,"text":"70244045 - 2023 - Unstructured-grid approach to develop high-fidelity groundwater model to understand groundwater flow and storage responses to excessive groundwater withdrawals in the Southern Hills aquifer system in southeastern Louisiana (USA)","interactions":[],"lastModifiedDate":"2023-05-31T14:30:11.069748","indexId":"70244045","displayToPublicDate":"2023-02-22T09:26:01","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3823,"text":"Journal of Hydrology: Regional Studies","active":true,"publicationSubtype":{"id":10}},"title":"Unstructured-grid approach to develop high-fidelity groundwater model to understand groundwater flow and storage responses to excessive groundwater withdrawals in the Southern Hills aquifer system in southeastern Louisiana (USA)","docAbstract":"<p><strong>Study region</strong></p><p>The Southern Hills aquifer system in the Louisiana Capital Area Groundwater Conservation District (CAGCD), USA.</p><p><strong>Study focus</strong></p><p>The Southern Hills aquifer system provides abundant groundwater for public and industrial supplies in the CAGCD. Groundwater depletion, saltwater intrusion, and land subsidence are potential concerns due to prolonged excessive groundwater withdrawals. This study develops a high-fidelity groundwater flow model utilizing a complex unstructured grid to investigate groundwater flow and storage responses to excessive groundwater withdrawals for the <span>Southern Hills aquifer system</span> in the CAGCD. The groundwater model incorporates the Mississippi River alluvial aquifer down to the Miocene sands extending to depths around 1 km.</p><p><strong>New hydrological insights</strong><br></p><p>Groundwater modeling results indicate large cones of depression in the Evangeline and Jasper formations in the Baton Rouge area due to prolonged groundwater withdrawals. Low-permeability faults are inferred by significant groundwater level difference across the faults. While local groundwater storage depletion in deeper aquifers is evident, overall estimated groundwater storage changes of the <span>Southern Hills aquifer system</span> in the CAGCD are close to zero in the past two decades, indicating insignificant groundwater storage changes. This is attributed to dominant interactions between the major rivers and the shallower alluvial aquifer. In addition, the simulated groundwater storage changes exhibit patterns similar to those derived by the Gravity Recovery and Climate Experiment (GRACE) model that has been used in evaluation of groundwater depletion in many regional studies.</p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.ejrh.2023.101342","usgsCitation":"Chen, Y., Vahdat-Aboueshagh, H., Tsai, F.T., Dausman, A., and Runge, M.C., 2023, Unstructured-grid approach to develop high-fidelity groundwater model to understand groundwater flow and storage responses to excessive groundwater withdrawals in the Southern Hills aquifer system in southeastern Louisiana (USA): Journal of Hydrology: Regional Studies, v. 46, 101342, 22 p., https://doi.org/10.1016/j.ejrh.2023.101342.","productDescription":"101342, 22 p.","ipdsId":"IP-137603","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":444389,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ejrh.2023.101342","text":"Publisher Index Page"},{"id":417579,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","otherGeospatial":"Southern Hills aquifer system","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -91.91720564327883,\n              31.007470903702682\n            ],\n            [\n              -91.91720564327883,\n              30.261535321867598\n            ],\n            [\n              -90.71125532149338,\n              30.261535321867598\n            ],\n            [\n              -90.71125532149338,\n              31.007470903702682\n            ],\n            [\n              -91.91720564327883,\n              31.007470903702682\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"46","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Chen, Ye-Hong","contributorId":305936,"corporation":false,"usgs":false,"family":"Chen","given":"Ye-Hong","email":"","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":874253,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Vahdat-Aboueshagh, Hamid","contributorId":305937,"corporation":false,"usgs":false,"family":"Vahdat-Aboueshagh","given":"Hamid","email":"","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":874254,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tsai, Frank T.-C.","contributorId":305938,"corporation":false,"usgs":false,"family":"Tsai","given":"Frank","email":"","middleInitial":"T.-C.","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":874255,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dausman, Alyssa","contributorId":223766,"corporation":false,"usgs":false,"family":"Dausman","given":"Alyssa","affiliations":[{"id":13499,"text":"The Water Institute of the Gulf","active":true,"usgs":false}],"preferred":false,"id":874256,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Runge, Michael C. 0000-0002-8081-536X mrunge@usgs.gov","orcid":"https://orcid.org/0000-0002-8081-536X","contributorId":3358,"corporation":false,"usgs":true,"family":"Runge","given":"Michael","email":"mrunge@usgs.gov","middleInitial":"C.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":874257,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70240217,"text":"ofr20221121 - 2023 - Observations of coastal circulation, waves, and sediment transport along West Maui, Hawaiʻi (November 2017– March 2018), and modeling effects of potential watershed restoration on decreasing sediment loads to adjacent coral reefs","interactions":[],"lastModifiedDate":"2023-02-23T11:58:55.644522","indexId":"ofr20221121","displayToPublicDate":"2023-02-22T09:06:04","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2022-1121","displayTitle":"Observations of Coastal Circulation, Waves, and Sediment Transport Along West Maui, Hawaiʻi (November 2017– March 2018), and Modeling Effects of Potential Watershed Restoration on Decreasing Sediment Loads to Adjacent Coral Reefs","title":"Observations of coastal circulation, waves, and sediment transport along West Maui, Hawaiʻi (November 2017– March 2018), and modeling effects of potential watershed restoration on decreasing sediment loads to adjacent coral reefs","docAbstract":"<p>Terrestrial sediment discharging from watersheds off West Maui, Hawaiʻi, has been documented as a primary stressor to local coral reefs, causing coral reef health to decline. The U.S. Geological Survey acquired and analyzed physical oceanographic and sedimentologic field data off the coast of West Maui to calibrate and validate physics-based, numerical hydrodynamic and sediment transport models of the study area developed by Deltares. These models simulated terrestrial sediment transport and dispersal from West Maui watersheds into coastal waters and how terrestrial sediment affects nearby coral reefs under different oceanographic forcing and watershed restoration scenarios.</p><p>Wave energy and near-bed turbidity are positively correlated in the field observations, illustrating a process not captured by the model simulations in which sediment already deposited on the seabed is resuspended by wave action and subsequently transported by prevailing currents. In the model simulations, large waves during flood events led to a decrease in suspended-sediment concentrations. Notably, however, the model results only consider sediment entering coastal waters from five stream sources and do not simulate sediment already present on the seabed.</p><p>The model simulations project that the Honokeana and Māhinahina coral reefs would experience the greatest reduction in sediment impacts from theoretical watershed restoration. Additionally, when large waves coincide with flood events, post-storm sedimentation generally decreases in the nearshore region, but increases in the region offshore of the reefs. The measured and modeled sediment dynamics demonstrate a demarcation between the coral reefs sheltered within embayments (Honolua reef) or behind points (Wahikuli reef) and those along the relatively open coastline between Kapalua and Kāʻanapali (Kapalua, Honokeana, Māhinahina, and Honokōwai reefs). The sheltered sites are affected by terrestrial sediment from single stream mouths, where most sediment is delivered within hours of a flood (rain) event. Once this sediment enters the nearshore, it settles out and remains within the reef area for a prolonged period owing to a lack of wave or current-driven bed shear stress. Thus, the primary effect of sediment on the reefs within these sheltered areas is sedimentation. In contrast, coral reefs along the unsheltered (or “open”) section of coastline (between Kapalua and Kāʻanapali) are more exposed to waves and terrestrial sediment from multiple stream sources. At these reefs, fine-grained terrestrial sediment can rarely settle but instead remains in suspension. Thus, even long after a flood event has occurred, these sites chronically experience light attenuation from suspended sediment.</p><p>These analyses underscore the importance of understanding how coastal ocean waves and circulation can lead to different sediment dynamics and stressors for coral reefs along the same region of the West Maui coastline. These differing factors indicate that the most effective watershed restoration and mitigation strategies may vary among the different coral reefs and streams. An important next step is to determine how the science of this study can support management goals for these coral reefs: what are target reductions of sedimentation, suspended-sediment concentrations, or the resulting light attenuation? Then, using the coupled hydrodynamic-sediment model, we can examine which watershed restoration scenarios in each stream will best achieve those targets.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221121","collaboration":"Prepared in cooperation with the Deltares Impacts of Extreme Weather Strategic Research Program","programNote":"Coastal and the Marine Hazards and Resources Program","usgsCitation":"Storlazzi, C.D., Cheriton, O.M., Cronin, K.M., van der Heijden, L.H., Winter, G., Rosenberger, K.J., Logan, J.B., and McCall, R.T., 2023, Observations of coastal circulation, waves, and sediment transport along West Maui, Hawaiʻi (November 2017–March 2018), and modeling effects of potential watershed restoration on decreasing sediment loads to adjacent coral reefs: U.S. Geological Survey Open-File Report 2022–1121, 73 p., https://doi.org/10.3133/ofr20221121.","productDescription":"Report: ix, 73 p.; 2 Data Releases","onlineOnly":"Y","ipdsId":"IP-138761","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":412766,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P914LMK2","text":"USGS data release","description":"USGS data release","linkHelpText":"Model parameter input files to compare effects of stream discharge scenarios on sediment deposition and concentrations around coral reefs off west Maui, Hawaii"},{"id":412765,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9DK9O60","text":"USGS data release","description":"USGS data release","linkHelpText":"Time series data of oceanographic conditions from West Maui, Hawaii, 2017-2018 Coral Reef Circulation and Sediment Dynamics Experiment"},{"id":412764,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1121/ofr20221121.pdf","text":"Report","size":"17.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1121"},{"id":412763,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1121/coverthb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"West Maui","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -156.72475140864907,\n              20.922050876041368\n            ],\n            [\n              -156.5888533113449,\n              20.922050876041368\n            ],\n            [\n              -156.5888533113449,\n              21.0514971765583\n            ],\n            [\n              -156.72475140864907,\n              21.0514971765583\n            ],\n            [\n              -156.72475140864907,\n              20.922050876041368\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","contact":"<p>Center Director, <a href=\"https://www.usgs.gov/centers/pcmsc\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov/centers/pcmsc\">Pacific Coastal and Marine Science Center</a><br>U.S. Geological Survey<br>2885 Mission Street<br>Santa Cruz, CA 95060</p>","tableOfContents":"<ul><li>Abstract</li><li>Introduction</li><li>Project Objectives</li><li>Description of Study Area</li><li>Field Operations</li><li>Hydrodynamic Model</li><li>Sediment Transport Model</li><li>Results</li><li>Modeled Sediment Transport</li><li>Discussion</li><li>Conclusions</li><li>References Cited</li></ul>","publishedDate":"2023-02-22","noUsgsAuthors":false,"publicationDate":"2023-02-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Storlazzi, Curt D. 0000-0001-8057-4490 cstorlazzi@usgs.gov","orcid":"https://orcid.org/0000-0001-8057-4490","contributorId":140584,"corporation":false,"usgs":true,"family":"Storlazzi","given":"Curt","email":"cstorlazzi@usgs.gov","middleInitial":"D.","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":863595,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cheriton, Olivia M. 0000-0003-3011-9136 ocheriton@usgs.gov","orcid":"https://orcid.org/0000-0003-3011-9136","contributorId":5476,"corporation":false,"usgs":true,"family":"Cheriton","given":"Olivia M.","email":"ocheriton@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":863596,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cronin, Katherine M. 0000-0003-3011-9136","orcid":"https://orcid.org/0000-0003-3011-9136","contributorId":302141,"corporation":false,"usgs":false,"family":"Cronin","given":"Katherine","email":"","middleInitial":"M.","affiliations":[{"id":36257,"text":"Deltares","active":true,"usgs":false}],"preferred":false,"id":863597,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"van der Heijden, Luuk H.","contributorId":302270,"corporation":false,"usgs":false,"family":"van der Heijden","given":"Luuk","email":"","middleInitial":"H.","affiliations":[{"id":36257,"text":"Deltares","active":true,"usgs":false}],"preferred":false,"id":863598,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Winter, Gundula","contributorId":204988,"corporation":false,"usgs":false,"family":"Winter","given":"Gundula","email":"","affiliations":[],"preferred":false,"id":863599,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rosenberger, Kurt J. 0000-0002-5185-5776 krosenberger@usgs.gov","orcid":"https://orcid.org/0000-0002-5185-5776","contributorId":140453,"corporation":false,"usgs":true,"family":"Rosenberger","given":"Kurt","email":"krosenberger@usgs.gov","middleInitial":"J.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":863600,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Logan, Joshua B. 0000-0002-6191-4119 jlogan@usgs.gov","orcid":"https://orcid.org/0000-0002-6191-4119","contributorId":2335,"corporation":false,"usgs":true,"family":"Logan","given":"Joshua","email":"jlogan@usgs.gov","middleInitial":"B.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":863601,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"McCall, Robert T.","contributorId":148986,"corporation":false,"usgs":false,"family":"McCall","given":"Robert","email":"","middleInitial":"T.","affiliations":[{"id":12474,"text":"Deltares, Netherlands","active":true,"usgs":false}],"preferred":false,"id":863602,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70240838,"text":"70240838 - 2023 - Modeling post-wildfire hydrologic response: Review and future directions for applications of physically based distributed simulation","interactions":[],"lastModifiedDate":"2023-02-24T13:08:09.195827","indexId":"70240838","displayToPublicDate":"2023-02-22T07:04:13","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5053,"text":"Earth's Future","active":true,"publicationSubtype":{"id":10}},"title":"Modeling post-wildfire hydrologic response: Review and future directions for applications of physically based distributed simulation","docAbstract":"<div class=\"article-section__content en main\"><p>Wildfire is a growing concern as climate shifts. The hydrologic effects of wildfire, which include elevated hazards and changes in water quantity and quality, are increasingly assessed using numerical models. Post-wildfire application of physically based distributed models provides unique insight into the underlying processes that affect water resources after wildfire. This work reviews and synthesizes post-wildfire applications of physically based distributed models by examining the scales and geographic/ecohydrologic distribution of model applications, hydrologic response process representation, model parameterization, and model performance metrics. Highlighted gaps and opportunities for advancing physically based distributed hydrologic response modeling after wildfire include the following: (a) applying models in under-represented geographic (S. America, Africa, Asia) and ecohydrologic regions (arid or dry subhumid climates), (b) incorporating all four major streamflow generation mechanisms (infiltration excess, saturation excess, subsurface storm flow, and groundwater flow), (c) representing integrated vadose zone and saturated zone processes to better capture subsurface streamflow generation, (d) building new remotely sensed model parameterization methods for precipitation interception, infiltration, and overland flow that account for burn severity and recovery, (e) incorporating distributed state variables (e.g., soil moisture, groundwater levels) in model performance assessment, (f) designing model intercomparison studies, including field datasets specifically for post-wildfire model development and validation, (g) linking mechanistic vegetation regrowth models with hydrologic models to improve simulation of process shifts as ecosystems recover, and (h) creating a new community modeling framework to integrate modeling advances across the wildfire science community.</p></div>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2022EF003038","usgsCitation":"Ebel, B., Shephard, Z.M., Walvoord, M.A., Murphy, S.F., Partridge, T.F., and Perkins, K., 2023, Modeling post-wildfire hydrologic response: Review and future directions for applications of physically based distributed simulation: Earth's Future, v. 11, e2022EF003038, 23 p., https://doi.org/10.1029/2022EF003038.","productDescription":"e2022EF003038, 23 p.","ipdsId":"IP-142611","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":444393,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2022ef003038","text":"Publisher Index Page"},{"id":413398,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11","noUsgsAuthors":false,"publicationDate":"2023-02-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Ebel, Brian A. 0000-0002-5413-3963","orcid":"https://orcid.org/0000-0002-5413-3963","contributorId":211845,"corporation":false,"usgs":true,"family":"Ebel","given":"Brian A.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":865024,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shephard, Zachary M. 0000-0003-2994-3355","orcid":"https://orcid.org/0000-0003-2994-3355","contributorId":222581,"corporation":false,"usgs":true,"family":"Shephard","given":"Zachary","email":"","middleInitial":"M.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":865025,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Walvoord, Michelle A. 0000-0003-4269-8366","orcid":"https://orcid.org/0000-0003-4269-8366","contributorId":211843,"corporation":false,"usgs":true,"family":"Walvoord","given":"Michelle","email":"","middleInitial":"A.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":865026,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Murphy, Sheila F. 0000-0002-5481-3635 sfmurphy@usgs.gov","orcid":"https://orcid.org/0000-0002-5481-3635","contributorId":1854,"corporation":false,"usgs":true,"family":"Murphy","given":"Sheila","email":"sfmurphy@usgs.gov","middleInitial":"F.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":865027,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Partridge, Trevor Fuess 0000-0003-1589-4783","orcid":"https://orcid.org/0000-0003-1589-4783","contributorId":302668,"corporation":false,"usgs":true,"family":"Partridge","given":"Trevor","email":"","middleInitial":"Fuess","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":865028,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Perkins, Kimberlie 0000-0001-8349-447X kperkins@usgs.gov","orcid":"https://orcid.org/0000-0001-8349-447X","contributorId":138544,"corporation":false,"usgs":true,"family":"Perkins","given":"Kimberlie","email":"kperkins@usgs.gov","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":865029,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70240920,"text":"70240920 - 2023 - Geothermal energy production adversely affects a sensitive indicator species within sagebrush ecosystems in western North America","interactions":[],"lastModifiedDate":"2023-03-01T12:54:36.468408","indexId":"70240920","displayToPublicDate":"2023-02-22T06:52:07","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1015,"text":"Biological Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Geothermal energy production adversely affects a sensitive indicator species within sagebrush ecosystems in western North America","docAbstract":"<p><span>Growing demand for renewable energy has resulted in expansion of energy infrastructure across sagebrush ecosystems of western North America. Geothermal power is an increasingly popular renewable energy source, especially within remote areas, but little is known about the impacts it may have on local wildlife populations. Investigations are warranted given similarities to more conventional surface disturbance activities with well-documented impacts. Using a novel 2-pronged analytical approach, we estimated effects of geothermal energy production activities (hereafter, geothermal) on populations of greater sage-grouse (</span><i>Centrocercus urophasianus</i><span>; hereafter, sage-grouse), a species of high conservation concern. First, we applied a before-after-control-impact paired series design at two geothermal sites in Nevada, USA, to estimate absence rates of male sage-grouse from lek sites (breeding grounds) and changes in predicted apparent abundance (</span><span class=\"math\"><span id=\"MathJax-Element-1-Frame\" class=\"MathJax_SVG\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><mover accent=&quot;true&quot; is=&quot;true&quot;><mi is=&quot;true&quot;>&amp;#x3BB;</mi><mo stretchy=&quot;true&quot; is=&quot;true&quot;>&amp;#x302;</mo></mover></math>\"><span class=\"MJX_Assistive_MathML\">�̂</span></span></span><span>) in relation to geothermal energy infrastructure. We then estimated effects of geothermal energy infrastructure and other environmental covariates on demographic rates. We found&nbsp;</span><span class=\"math\"><span id=\"MathJax-Element-2-Frame\" class=\"MathJax_SVG\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><mover accent=&quot;true&quot; is=&quot;true&quot;><mi is=&quot;true&quot;>&amp;#x3BB;</mi><mo stretchy=&quot;true&quot; is=&quot;true&quot;>&amp;#x302;</mo></mover></math>\"><span class=\"MJX_Assistive_MathML\">�̂</span></span></span><span>&nbsp;declined ∼24&nbsp;% within 5&nbsp;km of geothermal sites, while lek absence rates (e.g., indicating local extirpation) increased by ∼730&nbsp;% within 2&nbsp;km. Our demographic models revealed decreased nest survival in association with proximity to geothermal infrastructure, reduced topographic impedance surface (TIS; a proxy for sound and light dispersion emanating from geothermal infrastructure), and increased density of common ravens (</span><i>Corvus corax</i><span>), an effective nest predator. Models also estimated decreases in adult survival in relation to TIS. Finally, we applied population matrix models within a quantitative decision support framework to help guide locations for future geothermal development that balance the need for domestic energy production while minimizing adverse effects on wildlife populations.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.biocon.2022.109889","usgsCitation":"Coates, P.S., Prochazka, B.G., O’Neil, S.T., Webster, S.C., Espinosa, S., Ricca, M.A., Mathews, S.R., Casazza, M.L., and Delehanty, D.J., 2023, Geothermal energy production adversely affects a sensitive indicator species within sagebrush ecosystems in western North America: Biological Conservation, v. 280, 109889, 10 p., https://doi.org/10.1016/j.biocon.2022.109889.","productDescription":"109889, 10 p.","ipdsId":"IP-133911","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":444396,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.biocon.2022.109889","text":"Publisher Index Page"},{"id":413526,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"280","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"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":865299,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":865300,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"O’Neil, Shawn T. 0000-0002-0899-5220","orcid":"https://orcid.org/0000-0002-0899-5220","contributorId":206589,"corporation":false,"usgs":true,"family":"O’Neil","given":"Shawn","email":"","middleInitial":"T.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":865301,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Webster, Sarah C. 0000-0003-4981-2010","orcid":"https://orcid.org/0000-0003-4981-2010","contributorId":302117,"corporation":false,"usgs":true,"family":"Webster","given":"Sarah","email":"","middleInitial":"C.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":865302,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Espinosa, Shawn","contributorId":191084,"corporation":false,"usgs":false,"family":"Espinosa","given":"Shawn","affiliations":[],"preferred":false,"id":865303,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ricca, Mark A. 0000-0003-1576-513X mark_ricca@usgs.gov","orcid":"https://orcid.org/0000-0003-1576-513X","contributorId":139103,"corporation":false,"usgs":true,"family":"Ricca","given":"Mark","email":"mark_ricca@usgs.gov","middleInitial":"A.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":865304,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Mathews, Steven R. 0000-0002-3165-9460 smathews@usgs.gov","orcid":"https://orcid.org/0000-0002-3165-9460","contributorId":176922,"corporation":false,"usgs":true,"family":"Mathews","given":"Steven","email":"smathews@usgs.gov","middleInitial":"R.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":865305,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Casazza, Michael L. 0000-0002-5636-735X mike_casazza@usgs.gov","orcid":"https://orcid.org/0000-0002-5636-735X","contributorId":2091,"corporation":false,"usgs":true,"family":"Casazza","given":"Michael","email":"mike_casazza@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":865306,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Delehanty, David J.","contributorId":195584,"corporation":false,"usgs":false,"family":"Delehanty","given":"David","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":865307,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70240974,"text":"70240974 - 2023 - Vulnerability to climate change of managed stocks in the California Current large marine ecosystem","interactions":[],"lastModifiedDate":"2023-03-03T14:19:06.622212","indexId":"70240974","displayToPublicDate":"2023-02-21T08:13:02","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3912,"text":"Frontiers in Marine Science","onlineIssn":"2296-7745","active":true,"publicationSubtype":{"id":10}},"title":"Vulnerability to climate change of managed stocks in the California Current large marine ecosystem","docAbstract":"<div class=\"JournalAbstract\"><p><strong>Introduction:</strong><span>&nbsp;</span>Understanding how abundance, productivity and distribution of individual species may respond to climate change is a critical first step towards anticipating alterations in marine ecosystem structure and function, as well as developing strategies to adapt to the full range of potential changes.</p><p><strong>Methods:</strong><span>&nbsp;</span>This study applies the NOAA (National Oceanic and Atmospheric Administration) Fisheries Climate Vulnerability Assessment method to 64 federally-managed species in the California Current Large Marine Ecosystem to assess their vulnerability to climate change, where vulnerability is a function of a species’ exposure to environmental change and its biological sensitivity to a set of environmental conditions, which includes components of its resiliency and adaptive capacity to respond to these new conditions.</p><p><strong>Results:</strong><span>&nbsp;</span>Overall, two-thirds of the species were judged to have Moderate or greater vulnerability to climate change, and only one species was anticipated to have a positive response. Species classified as Highly or Very Highly vulnerable share one or more characteristics including: 1) having complex life histories that utilize a wide range of freshwater and marine habitats; 2) having habitat specialization, particularly for areas that are likely to experience increased hypoxia; 3) having long lifespans and low population growth rates; and/or 4) being of high commercial value combined with impacts from non-climate stressors such as anthropogenic habitat degradation. Species with Low or Moderate vulnerability are either habitat generalists, occupy deep-water habitats or are highly mobile and likely to shift their ranges.</p><p><strong>Discussion:</strong><span>&nbsp;</span>As climate-related changes intensify, this work provides key information for both scientists and managers as they address the long-term sustainability of fisheries in the region. This information can inform near-term advice for prioritizing species-level data collection and research on climate impacts, help managers to determine when and where a precautionary approach might be warranted, in harvest or other management decisions, and help identify habitats or life history stages that might be especially effective to protect or restore.</p></div>","language":"English","publisher":"Frontiers Media","doi":"10.3389/fmars.2023.1103767","usgsCitation":"McClure, M., Haltuch, M.A., Willis-Norton, E., Huff, D.D., Hazen, E.L., Crozier, L.G., Jacox, M.G., Nelson, M.W., Andrews, K.S., Barnett, L.A., Berger, A.M., Beyer, S., Bizzarro, J., Boughton, D.A., Cope, J.M., Carr, M.H., Dewar, H., Dick, E., Emmanis, D., Dunham, J., Gertseva, V., Greene, C.M., Gustafson, R.G., S., H.O., Harvey, C., Henderson, M., Jordan, C.E., Kaplan, I., Lindley, S.T., Mantua, N., Matson, S.E., Monk, M.H., Moyle, P.B., Nicol, C., Pohl, J., Rykaczewski, R.R., Samhouri, J.F., Sogard, S., Tolimieri, N., Wallace, J., Wetzel, C., and Bograd, S.J., 2023, Vulnerability to climate change of managed stocks in the California Current large marine ecosystem: Frontiers in Marine Science, v. 10, 1103767, 21 p., https://doi.org/10.3389/fmars.2023.1103767.","productDescription":"1103767, 21 p.","ipdsId":"IP-148260","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":444398,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fmars.2023.1103767","text":"Publisher Index Page"},{"id":413657,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Oregon, Washington","otherGeospatial":"California Current Large Marine Ecosystem","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        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,{"id":70240937,"text":"70240937 - 2023 - Qualitative value of information provides a transparent and repeatable method for identifying critical uncertainty","interactions":[],"lastModifiedDate":"2023-06-09T15:10:18.526568","indexId":"70240937","displayToPublicDate":"2023-02-21T07:16:48","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"Qualitative value of information provides a transparent and repeatable method for identifying critical uncertainty","docAbstract":"<p>Conservation decisions are often made in the face of uncertainty because the urgency to act can preclude delaying management while uncertainty is resolved. In this context, adaptive management is attractive, allowing simultaneous management and learning. An adaptive program design requires the identification of critical uncertainties that impede the choice of management action. Quantitative evaluation of critical uncertainty, using the expected value of information, may require more resources than are available in the early stages of conservation planning. Here, we demonstrate the use of a qualitative index to the value of information (QVoI) to prioritize which sources of uncertainty to reduce regarding the use of prescribed fire to benefit Eastern Black Rails (<i>Laterallus jamaicensis jamaicensis</i>), Yellow Rails (<i>Coterminous noveboracensis</i>), and Mottled Ducks (<i>Anas fulvigula</i>; hereafter, focal species) in high marshes of the U.S. Gulf of Mexico. Prescribed fire has been used as a management tool in Gulf of Mexico high marshes throughout the last 30+ years; however, effects of periodic burning on the focal species and the optimal conditions for burning marshes to improve habitat remain unknown. We followed a structured decision-making framework to develop conceptual models, which we then used to identify sources of uncertainty and articulate alternative hypotheses about prescribed fire in high marshes. We used QVoI to evaluate the sources of uncertainty based on their magnitude, relevance for decision making, and reducibility. We found that hypotheses related to the optimal fire return interval and season were the highest priorities for study, whereas hypotheses related to predation rates and interactions among management techniques were lowest. These results suggest that learning about the optimal fire frequency and season to benefit the focal species might produce the greatest management benefit. In this case study, we demonstrate that QVoI can help managers decide where to apply limited resources to learn which specific actions will result in a higher likelihood of achieving the desired management objectives. Further, we summarize the strengths and limitations of QVoI and outline recommendations for its future use for prioritizing research to reduce uncertainty about system dynamics and the effects of management actions.</p>","language":"English","publisher":"Ecological Society of America","doi":"10.1002/eap.2824","usgsCitation":"Stantial, M.L., Lawson, A.J., Fournier, A., Kappes, P.J., Kross, C.S., Runge, M.C., Woodrey, M.S., and Lyons, J.E., 2023, Qualitative value of information provides a transparent and repeatable method for identifying critical uncertainty: Ecological Applications, v. 33, no. 4, e2824, 15 p., https://doi.org/10.1002/eap.2824.","productDescription":"e2824, 15 p.","ipdsId":"IP-138568","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":444400,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/eap.2824","text":"Publisher Index Page"},{"id":435440,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P95OCH4K","text":"USGS data release","linkHelpText":"Qualitative value of information for the effects of prescribed fire in Gulf of Mexico marshes: Expert judgment scores from a 2020 adaptive management workshop"},{"id":413613,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"33","issue":"4","noUsgsAuthors":false,"publicationDate":"2023-03-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Stantial, Michelle L 0000-0003-1112-2903","orcid":"https://orcid.org/0000-0003-1112-2903","contributorId":291453,"corporation":false,"usgs":true,"family":"Stantial","given":"Michelle","email":"","middleInitial":"L","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":865361,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lawson, Abigail Jean 0000-0002-2799-8750","orcid":"https://orcid.org/0000-0002-2799-8750","contributorId":276319,"corporation":false,"usgs":true,"family":"Lawson","given":"Abigail","email":"","middleInitial":"Jean","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":865362,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fournier, Auriel 0000-0002-8530-9968","orcid":"https://orcid.org/0000-0002-8530-9968","contributorId":261669,"corporation":false,"usgs":false,"family":"Fournier","given":"Auriel","email":"","affiliations":[{"id":36403,"text":"University of Illinois","active":true,"usgs":false}],"preferred":false,"id":865363,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kappes, Peter J.","contributorId":275193,"corporation":false,"usgs":false,"family":"Kappes","given":"Peter","email":"","middleInitial":"J.","affiliations":[{"id":25426,"text":"OSU","active":true,"usgs":false}],"preferred":false,"id":865364,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kross, Chelsea S. 0000-0003-4959-2556","orcid":"https://orcid.org/0000-0003-4959-2556","contributorId":302753,"corporation":false,"usgs":false,"family":"Kross","given":"Chelsea","email":"","middleInitial":"S.","affiliations":[{"id":65542,"text":"Forbes Biological Station–Bellrose Waterfowl Research Center, Illinois Natural History Survey, Prairie Research Institute, University of Illinois at Urbana-Champaign","active":true,"usgs":false}],"preferred":false,"id":865365,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Runge, Michael C. 0000-0002-8081-536X mrunge@usgs.gov","orcid":"https://orcid.org/0000-0002-8081-536X","contributorId":3358,"corporation":false,"usgs":true,"family":"Runge","given":"Michael","email":"mrunge@usgs.gov","middleInitial":"C.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":865366,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Woodrey, Mark S.","contributorId":259212,"corporation":false,"usgs":false,"family":"Woodrey","given":"Mark","email":"","middleInitial":"S.","affiliations":[{"id":17848,"text":"Mississippi State University","active":true,"usgs":false}],"preferred":false,"id":865367,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Lyons, James E. 0000-0002-9810-8751","orcid":"https://orcid.org/0000-0002-9810-8751","contributorId":222844,"corporation":false,"usgs":true,"family":"Lyons","given":"James","email":"","middleInitial":"E.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":865368,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70242885,"text":"70242885 - 2023 - Spatial and temporal analysis of geologic slip rates, Cucamonga Fault, California, USA: Implications for along-strike applications and multi-fault rupture","interactions":[],"lastModifiedDate":"2024-06-27T16:55:59.264089","indexId":"70242885","displayToPublicDate":"2023-02-21T06:49:54","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":6453,"text":"Journal of Geophysical Research Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"Spatial and temporal analysis of geologic slip rates, Cucamonga Fault, California, USA: Implications for along-strike applications and multi-fault rupture","docAbstract":"<div class=\"article-section__content en main\"><p>To constrain fault processes and hazard, fault slip rates may be extrapolated over different fault lengths or time intervals. Here, we investigate slip rates for the Cucamonga Fault (CF). The CF is located at the junction of the Transverse Range fault system with the San Andreas and San Jacinto Faults, and it is hypothesized to connect with these faults, promoting the propagation of large, multi-fault earthquakes. Previous work has shown that CF displacements on late Quaternary alluvial fan surfaces are highly variable along strike. We present two new<span>&nbsp;</span><sup>10</sup>Be surface exposure ages from depth profiles on the alluvial fans. Slip rates are consistent with a rate of 1.4&nbsp;±&nbsp;0.3&nbsp;m/kyr over time intervals of ∼20, ∼30, and ∼40&nbsp;kyr. If the CF participates in multi-fault ruptures, then these earthquakes occur either rarely or with sufficient regularity to maintain apparently steady rates over multiple intervals. We also explore along-strike fault displacement variability using a calibrated morphological model. The model successfully reproduces scarp profiles and indicates that fault displacement variability can be explained in part by scarp age but not uplift rate. We infer that both erosion by ephemeral gullying and distributed deformation contribute to fault displacement variability, although both are difficult to detect confidently without excavations across the scarp. These investigations show that better characterization of cumulative-slip variability along strike may improve accuracy and precision of slip rates. Slip rates that do not consider epistemic uncertainties may not be suitable for extrapolation over longer fault sections.</p></div>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2022JB024942","usgsCitation":"McPhillips, D., and Scharer, K., 2023, Spatial and temporal analysis of geologic slip rates, Cucamonga Fault, California, USA: Implications for along-strike applications and multi-fault rupture: Journal of Geophysical Research Solid Earth, v. 128, no. 3, e2022JB024942, 23 p., https://doi.org/10.1029/2022JB024942.","productDescription":"e2022JB024942, 23 p.","ipdsId":"IP-140904","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":498004,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2022jb024942","text":"Publisher Index Page"},{"id":435441,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9453JT4","text":"USGS data release","linkHelpText":"Data release for spatial and temporal analysis of geologically derived fault slip rates, Cucamonga Fault, California, USA"},{"id":416112,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -119.27105227256959,\n              34.32741997760887\n            ],\n            [\n              -119.27105227256959,\n              33.589632675582635\n            ],\n            [\n              -116.415835160349,\n              33.589632675582635\n            ],\n            [\n              -116.415835160349,\n              34.32741997760887\n            ],\n            [\n              -119.27105227256959,\n              34.32741997760887\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"128","issue":"3","noUsgsAuthors":false,"publicationDate":"2023-02-28","publicationStatus":"PW","contributors":{"authors":[{"text":"McPhillips, Devin 0000-0003-1987-9249","orcid":"https://orcid.org/0000-0003-1987-9249","contributorId":217362,"corporation":false,"usgs":true,"family":"McPhillips","given":"Devin","email":"","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":870097,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Scharer, Katherine M. 0000-0003-2811-2496","orcid":"https://orcid.org/0000-0003-2811-2496","contributorId":217361,"corporation":false,"usgs":true,"family":"Scharer","given":"Katherine M.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":870098,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70240758,"text":"70240758 - 2023 - The 2013−2020 seismic activity at Sabancaya Volcano (Peru): Long lasting unrest and eruption","interactions":[],"lastModifiedDate":"2023-02-21T01:45:59.585247","indexId":"70240758","displayToPublicDate":"2023-02-20T19:36:36","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2499,"text":"Journal of Volcanology and Geothermal Research","active":true,"publicationSubtype":{"id":10}},"title":"The 2013−2020 seismic activity at Sabancaya Volcano (Peru): Long lasting unrest and eruption","docAbstract":"<p id=\"sp0075\">Sabancaya volcano is the youngest and second most active volcano in Peru. It is part of the Ampato-Sabancaya volcanic complex which sits to the south of the ancient Hualca Hualca volcano and several frequently active faults, thus resulting in complex volcano-tectonic interactions. After 15&nbsp;years of repose, in 2013, a series of 4 earthquakes with magnitude &gt;4.5 occurred within 24&nbsp;h, marking the beginning of a new episode of unrest. Several additional swarms of earthquakes occurred in the following years until magmatic eruptive activity started on 6 November 2016. This activity is ongoing as of this writing, with an average of 50 explosions per day. In this study, we present results of multiparametric monitoring of Sabancaya's activity observed during 2013–2020. Seismic data are used to create a one-dimensional seismic velocity model, to catalog, locate, and characterize earthquakes, to detect repeating earthquake families, and to monitor seismic velocity variations by ambient noise cross-correlation. These analyses are complemented by visual and remote sensing observations and ground deformation measurements. All monitored parameters showed significant changes on 6 November 2016, the day of eruption onset, thus dividing the eruptive activity into pre-eruptive and eruptive stages.</p><p id=\"sp0080\">The unrest is characterized by high levels of seismic activity with hundreds of events detected per day. Volcano-tectonic (VT) earthquakes were dominant during the pre-eruptive period while long-period (LP) events and explosions have been most numerous since the eruption onset. Earthquake locations highlight long-lasting seismogenic zones along multiple previously active regional faults, as well as along newly identified faults. This VT seismicity is mainly distributed in a sector from the northwest to the east of the volcanic complex at distances of up to 30&nbsp;km from the crater. We focus our analysis on two eruptive episodes: the eruption onset and subsequent crater migration from south to north, and the increase of lava dome extrusion rate in 2019. Both episodes are accompanied by seismic velocity decreases of up to 0.2% and are preceded by a few weeks by bursts of distal VT activity, including numerous repeating earthquakes. These repeated events were located on several remote tectonic faults (5–25&nbsp;km from the vent). We suggest that these phenomena could be due to the injection of a batch of magma in the deep reservoir and/or conduit, which would generate 1) a pressure wave propagating in the hydrothermal system, triggering the bursts of seismic activity and 2) slow rising of magma by melting old material filling the conduit that eventually produced the eruptive and dome growth acceleration events.</p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jvolgeores.2023.107767","usgsCitation":"Machacca, R., Lesage, P., Tavera, H., Pesicek, J., Caudron, C., Torres, J., Puma, N., Vargas, K., Lazarte, I., Rivera, M., and Burgisser, A., 2023, The 2013−2020 seismic activity at Sabancaya Volcano (Peru): Long lasting unrest and eruption: Journal of Volcanology and Geothermal Research, v. 435, 107767, 21 p., https://doi.org/10.1016/j.jvolgeores.2023.107767.","productDescription":"107767, 21 p.","ipdsId":"IP-149045","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":444409,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jvolgeores.2023.107767","text":"Publisher Index Page"},{"id":413229,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Peru","otherGeospatial":"Andes Mountains, Sabancaya Volcano","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -71.88759125278847,\n              -15.796325861968512\n            ],\n            [\n              -71.87969027972629,\n              -15.806737845832032\n            ],\n            [\n              -71.86380245345819,\n              -15.818058204597975\n            ],\n            [\n              -71.82223646473676,\n              -15.826238215481283\n          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Perú","active":true,"usgs":false}],"preferred":false,"id":864724,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lesage, P.","contributorId":302573,"corporation":false,"usgs":false,"family":"Lesage","given":"P.","email":"","affiliations":[{"id":63992,"text":"Université Grenoble Alpes","active":true,"usgs":false}],"preferred":false,"id":864725,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tavera, H.","contributorId":302574,"corporation":false,"usgs":false,"family":"Tavera","given":"H.","email":"","affiliations":[{"id":65510,"text":"Instituto Geofísico del Perú","active":true,"usgs":false}],"preferred":false,"id":864726,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pesicek, J.D. 0000-0001-7964-5845","orcid":"https://orcid.org/0000-0001-7964-5845","contributorId":72233,"corporation":false,"usgs":true,"family":"Pesicek","given":"J.D.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":864727,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Caudron, C.","contributorId":302575,"corporation":false,"usgs":false,"family":"Caudron","given":"C.","affiliations":[{"id":65511,"text":"Université libre de Bruxelles","active":true,"usgs":false}],"preferred":false,"id":864728,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Torres, J.L.","contributorId":302576,"corporation":false,"usgs":false,"family":"Torres","given":"J.L.","email":"","affiliations":[{"id":65510,"text":"Instituto Geofísico del Perú","active":true,"usgs":false}],"preferred":false,"id":864729,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Puma, N.","contributorId":302577,"corporation":false,"usgs":false,"family":"Puma","given":"N.","affiliations":[{"id":65510,"text":"Instituto Geofísico del Perú","active":true,"usgs":false}],"preferred":false,"id":864730,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Vargas, K.","contributorId":302578,"corporation":false,"usgs":false,"family":"Vargas","given":"K.","email":"","affiliations":[{"id":65510,"text":"Instituto Geofísico del Perú","active":true,"usgs":false}],"preferred":false,"id":864731,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Lazarte, I.","contributorId":302579,"corporation":false,"usgs":false,"family":"Lazarte","given":"I.","affiliations":[{"id":65510,"text":"Instituto Geofísico del Perú","active":true,"usgs":false}],"preferred":false,"id":864732,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Rivera, M.","contributorId":302580,"corporation":false,"usgs":false,"family":"Rivera","given":"M.","email":"","affiliations":[{"id":65510,"text":"Instituto Geofísico del Perú","active":true,"usgs":false}],"preferred":false,"id":864733,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Burgisser, Alain","contributorId":152269,"corporation":false,"usgs":false,"family":"Burgisser","given":"Alain","email":"","affiliations":[{"id":18894,"text":"Universite de Savoie- CNRS, ISTerre","active":true,"usgs":false}],"preferred":false,"id":864753,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}}
,{"id":70240759,"text":"70240759 - 2023 - Pelagic food web interactions in a large invaded ecosystem: Implications for reintroducing a native top predator","interactions":[],"lastModifiedDate":"2023-06-09T15:08:17.577235","indexId":"70240759","displayToPublicDate":"2023-02-20T19:24:27","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1471,"text":"Ecology of Freshwater Fish","active":true,"publicationSubtype":{"id":10}},"title":"Pelagic food web interactions in a large invaded ecosystem: Implications for reintroducing a native top predator","docAbstract":"<p><span>A series of species introductions, overexploitation, and habitat modification preceded the extirpation of Lahontan cutthroat trout (</span><i>Oncorhynchus clarkii</i><span>&nbsp;henshawi; LCT), historically the apex predator, from Lake Tahoe, California-Nevada, USA. Studies evaluating limiting factors for LCT emphasise the need to elucidate food web interactions, yet important knowledge gaps regarding trophic interactions among nonnative pelagic fishes and invertebrates remain. We quantified the abundance and consumption demand of planktivores with an emphasis on kokanee (</span><i>Oncorhynchus nerka</i><span>) and&nbsp;</span><i>Mysis diluviana</i><span>. We synthesised this new information with existing information for lake trout (</span><i>Salvelinus namaycush</i><span>). The seasonal supply of copepods satisfied the consumption demand of kokanee, but only supported low feeding and growth rates. Kokanee relied heavily on&nbsp;</span><i>Mysis</i><span>&nbsp;as prey, an unusual result.&nbsp;</span><i>Mysis</i><span>&nbsp;exhibited a high degree of herbivory initially followed by heavier consumption on copepods by larger individuals. Consumption demand for&nbsp;</span><i>Mysis</i><span>&nbsp;on copepods exceeded that of kokanee during all seasons.&nbsp;</span><i>Mysis</i><span>&nbsp;contributed to over 50% of the annual energy budget for lake trout up to 625 mm. Consumption of&nbsp;</span><i>Mysis</i><span>&nbsp;by lake trout and kokanee represented a significant source of mortality when compared to the production of&nbsp;</span><i>Mysis</i><span>. Predation on kokanee was sustainable, only involved lake trout &gt;625 mm, and was focused on prespawning aggregations. Despite the presence of&nbsp;</span><i>Mysis</i><span>-fueled lake trout, kokanee have persisted; a noteworthy pattern when considering the negative responses of kokanee to nonnative lake trout and&nbsp;</span><i>Mysis</i><span>&nbsp;observed elsewhere. This pattern suggests that there may still be an effective niche for LCT in the invaded Lake Tahoe ecosystem.</span></p>","language":"English","publisher":"John Wiley & Sons, Inc.","doi":"10.1111/eff.12706","usgsCitation":"Hansen, A.G., McCoy, A., Thiede, G., and Beauchamp, D., 2023, Pelagic food web interactions in a large invaded ecosystem: Implications for reintroducing a native top predator: Ecology of Freshwater Fish, v. 32, no. 3, p. 552-570, https://doi.org/10.1111/eff.12706.","productDescription":"19 p.","startPage":"552","endPage":"570","ipdsId":"IP-147438","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":499263,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/eff.12706","text":"Publisher Index Page"},{"id":413228,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Nevada","otherGeospatial":"Lake Tahoe","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -119.9928593695287,\n              38.91420593218916\n            ],\n            [\n              -119.94067431093485,\n              38.9505270086465\n            ],\n            [\n              -119.9420476019504,\n              38.99003174862847\n            ],\n            [\n              -119.93655443788818,\n              39.05404664405532\n            ],\n            [\n              -119.92831469179416,\n              39.065776420173194\n            ],\n            [\n              -119.9310612738256,\n              39.10521681856693\n            ],\n            [\n              -119.94479418398184,\n              39.1148070943255\n            ],\n            [\n              -119.92144823671603,\n        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Collins, Colorado 80526, USA","active":true,"usgs":false}],"preferred":false,"id":864734,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McCoy, Allison","contributorId":302581,"corporation":false,"usgs":false,"family":"McCoy","given":"Allison","email":"","affiliations":[{"id":65512,"text":"Washington Cooperative Fish and Wildlife Research Unit, School of Aquatic and Fishery Sciences, University of Washington, Box 355020, Seattle, Washington 98195, USA","active":true,"usgs":false}],"preferred":false,"id":864735,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thiede, Gary P.","contributorId":302582,"corporation":false,"usgs":false,"family":"Thiede","given":"Gary P.","affiliations":[{"id":65513,"text":"Department of Watershed Science and The Ecology Center, Utah State University, Logan, Utah 84322, USA","active":true,"usgs":false}],"preferred":false,"id":864736,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Beauchamp, David 0000-0002-3592-8381","orcid":"https://orcid.org/0000-0002-3592-8381","contributorId":217816,"corporation":false,"usgs":true,"family":"Beauchamp","given":"David","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":864737,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70240761,"text":"70240761 - 2023 - Flow–recruitment relationships for Shoal Chub and implications for managing environmental flows","interactions":[],"lastModifiedDate":"2023-11-07T14:56:20.584618","indexId":"70240761","displayToPublicDate":"2023-02-20T16:04:57","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"title":"Flow–recruitment relationships for Shoal Chub and implications for managing environmental flows","docAbstract":"<h3 id=\"nafm10837-sec-1001-title\" class=\"article-section__sub-title section1\">Objective</h3><p>Regulation of river flow regimes by dams and diversions impacts aquatic biota and ecosystems globally. However, our understanding of the ecological consequences of flow alteration and ecological benefits of flow restoration lags behind our ability to manipulate flows, and there is a need for broader development of flow–ecology relationships. Approaches for establishing flow–ecology relationships have recently shifted away from state-based methods that analyze snapshots of ecological conditions and towards rate-based methods focused on mechanisms that link hydrology with dynamics of important ecological components and processes.</p><h3 id=\"nafm10837-sec-2002-title\" class=\"article-section__sub-title section1\">Methods</h3><p>We used a rate-based approach to validate environmental flow standards developed for the lower Brazos River, Texas, by analyzing the relationship between flow regime components and recruitment strength of imperiled Shoal Chub<span>&nbsp;</span><i>Macrhybopsis hyostoma</i>, a fluvial specialist and pelagic-broadcast-spawning fish. We collected 254 age-0 Shoal Chub (9–40 mm total length), extracted their otoliths to estimate age in days, and used a generalized additive model to regress the number of captured recruits that hatched on a calendar date against flow regime metrics, such as pulse magnitude, flow rate of change, and pulse timing in relation to environmental flow standards proposed by a science advisory committee (Brazos Basin and Bay Area Expert Science Team).</p><h3 id=\"nafm10837-sec-3002-title\" class=\"article-section__sub-title section1\">Result</h3><p>The model revealed that flow magnitude, rate of change, and timing were all significant predictors that collectively explained 60% of variation in the recruitment strength index. Hindcasting for 1919–2020 showed a general reduction in recruitment strength following commencement of flow regulation in the lower Brazos River and revealed that high recruitment correlated with years in which most or all proposed flow tiers were attained, whereas low recruitment correlated with years when less than half of the targeted tiers were attained.</p><h3 id=\"nafm10837-sec-4002-title\" class=\"article-section__sub-title section1\">Conclusion</h3><p>Our work represents an effective validation method for environmental flow recommendations and reveals specific flow regimes that benefit an imperiled fish species.</p>","language":"English","publisher":"Wiley","doi":"10.1002/nafm.10837","usgsCitation":"Perkin, J., Acre, M.R., Ellard, J.K., Rodger, A.W., Trungale, J., Winemiller, K.O., and Yancy, L.E., 2023, Flow–recruitment relationships for Shoal Chub and implications for managing environmental flows: North American Journal of Fisheries Management, v. 43, no. 5, p. 1260-1275, https://doi.org/10.1002/nafm.10837.","productDescription":"16 p.","startPage":"1260","endPage":"1275","ipdsId":"IP-137319","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":413226,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Mexico, Texas","otherGeospatial":"Brazos River Basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -103.55664204856129,\n              34.891337132196966\n            ],\n            [\n              -103.67919574341136,\n              34.90431733940822\n            ],\n            [\n              -103.67460945809466,\n              33.88709425240866\n            ],\n            [\n              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Yet accurate mapping that captures local spatial variability and associated local controls on surface flow presence is limited. An empirical random-forest model was developed to predict streamflow permanence (late summer surface-flow presence) for Mount Rainier National Park and the surrounding mountainous area in western Washington, USA. This model was developed to improve upon the existing multi-state, regional-scale probability of stream permanence developed for the greater Pacific Northwest Region (PROSPER</span><sub>PNW</sub><span>). The model was trained on 544 wet/dry observations collected during the late summer, baseflow period from 2018 to 2020 using the crowd-source mobile application, FLOwPER. Final model accuracy was 0.74 with drainage area and covariates describing geology, topography, and land cover as top predictors of streamflow permanence compared to coarser resolution climatic covariates. The prevalence of static covariates over climatic covariates as top ranked important covariates highlights the importance of scale when evaluating controls on streamflow permanence. Cross validation of the model indicates that streamflow permanence probabilities from this model is an improvement over the regional-scale PROSPER</span><sub>PNW</sub><span>&nbsp;model demonstrating the utility of relatively simple, crowd-sourced data to address water resource needs, and that determination of important predictors of streamflow permanence is influenced by the spatial and temporal resolution of analysis.</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/hyp.14813","usgsCitation":"Jaeger, K.L., Sando, R., Dunn, S., and Gendaszek, A.S., 2023, Predicting probabilities of late summer surface flow presence in a glaciated mountainous headwater region: Hydrological Processes, v. 37, no. 2, e14813, 20 p., https://doi.org/10.1002/hyp.14813.","productDescription":"e14813, 20 p.","ipdsId":"IP-141066","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true},{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"links":[{"id":444412,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/hyp.14813","text":"Publisher Index Page"},{"id":435442,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P942QL23","text":"USGS data release","linkHelpText":"Supporting data for and predictions from streamflow permanence modeling in Mount Rainier National Park and surrounding area, Washington, 2018-2020"},{"id":413225,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Mt. 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